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Chapter 1Statistics（统计学）：研究数据资料的收集、整理、分析和解释（interpretation）的科学。
Biostatistics（生物统计学）：统计学应用于生物科学Variable（变量）：指某种特征，它的表现在不同个体间或不同组间存在变异性。
Observation（观测值）：指对变量的表现进行观察或测量所获得的数值，有时也被称为变数（variate）Population（总体）：又叫“统计总体”，是指一个统计问题研究对象的全体，它是具有某种（或某些）共同特征的元素的集合。
Individual（个体）：总体中每一个研究对象称作个体。
Sample（样本）：从总体中按一定方法抽取部分具有代表性的个体，这部分个体称为样本。
Parameter（参数）：描述总体特征的数，如总体平均数、总体方差等。
Statistic（统计量）：描述样本特征的量，如样本平均数、样本方差、样本相关系数等。
Accuracy（准确性）：指观测值或估计值与真值的接近程度。
Precision（精确性）：对同一物体的重复观察值或估计值彼此之间的接近程度。
Chapter 2Raw data（直接数据）:数据调查与实验未经处理的数据；Continuous data（连续性数据）：指在一定范围内可取任何实数值的数据。
Discrete data（离散性数据）：在一定范围内只能取有限种可能值的数据。
Count data（计数数据）：用计数的方式得到的数据资料，必须用整数来表示。
Classification data（分类资料）：可自然的或人为的分为2个或多个不同类别的资料。
例如：男生记做1 女生记做2频数（率）分布（frequency distribution）；；下四分位数（lower quartile）；中位数（median）；上四分位数（upper quartile）；条形图（bar chart）；直方图（histogram）；饼图（pie chart）；散点图（scatter plot），组间距（interval）Percentile（百分位数）：一组n个观测值按数值大小排列，小于某数值的数据个数占全体个数的x%,则为x%分位数。
再论中介模型滥⽤：如何规范地实施因果中介效应分析因果中介效应估计、敏感性分析、⼯具变量模型。
近年来，⼤量的经济学论⽂滥⽤中介效应模型，参考⽂献是⼀遍中⽂⼼理学论⽂，特别以硕⼠论⽂居多，引起严肃经济学者的警觉和批评。
在这个⽅程组中有很多的问题存在：y=a+bx+u (1)m=a1x+u1 (2)y=a2x+b2m+u2 (3）很显然（1）式中⾄少遗漏了中介变量m，则导致严重内⽣性问题，内⽣性导致b的估计是有偏的，b都估计不对，何谈后⾯的因果效应和机制分析的识别？且不说有没有考虑三个⼦⽅程的内⽣性问题了！令⼈悲哀和⽆免，其实只需要基本的初等计量经济学知识！本推⽂将介绍在因果分析框架下中介分析模型。
此外，管理学的调节效应其实就是规范实证经济学⾥⾯的交互项模型，即相关异质性因果效应分析：即将开幕的STATA前沿培训精讲：带异质性处理效应的双向固定效应估计|从精确断点、模糊断点估计的实际操作|弱⼯具变量稳健推断异质性分析、机制分析的内容可选择学习：即将开班 | 结构模型、Stata实证前沿、Python数据挖掘暑假⼯作坊当然，⽐较合理地机制分析是基于理论框架的科学分析，这也可以在以上暑假⼯作坊课程中的结构估计部分学习之，其也提供⽂本分析的内容。
欢迎咨询！Causal mediation analysisRaymond Hicks,Niehaus Center for Globalization and GovernancePrinceton University,Princeton, NJ,rhicks@Dustin Tingley,Department of Government,Harvard UniversityCambridge, MA,dtingley@Abstract. Estimating the mechanisms that connect explanatory variables with the explained variable, also known as “mediation analysis,” is central to a variety of social-science fields, especially psychology, and incre epidemiology.Recent work on the statistical methodology behind mediation analysis points to limitations in earlier methods. We implement in Stata computational approaches based on recent developments in the sta analysis. In particular, we provide functions for the correct calculation of causal mediation effects using several different types of parametric models, as well as the calculation of sensitivity analyses for violations to the required for interpreting mediation results causally.摘要：估计解释变量与被解释变量之间的联系机制，也被称为“中介分析”，是各种社会科学领域的核⼼，尤其是⼼理学，并逐渐成为流⾏病学等领域的核⼼。
1Introduction to strategic management accounting1.1I ntroduction to planning, control and decision making☞Strategic planning is the process of deciding on objectives of the organization, on changes in these objectives, on the resource to attain these objectives, and on the policies that are to govern the acquisition, use and disposition of these resources.☞Characteristics of strategic information⏹Long term and wide scope⏹Generally formulated in writing⏹Widely circulated广泛流传⏹Doesn’t trigger direct action, but series of lesser plans⏹Includes selection of products, purchase of non-current assets, required levels ofcompany profit☞Management control: the process by which management ensure that resources are obtained and used effectively and efficiently in the accomplishment of the organisation’s objectives. It is sometimes called tactics ad tactical planning.☞Characteristics of management accounting information⏹Short-term and non-strategic⏹Management control planning activities include preparing annual sales budget⏹Management control activities include ensuring budget targets are reached⏹Carried out in a series of routine and regular planning and comparison procedures⏹Management control information covers the whole organisation, is routinely collected,is often quantitative and commonly expressed in money terms (cash flow forecasts, variance analysis reports, staffing levels⏹Source of information likely to be endogenous内生的☞Characteristics of operational control⏹Short-term and non-strategic⏹Occurs in all aspects of an organisations activities and need for day to dayimplementation of plans⏹Often carried out at short notice⏹Information likely to have an endogenous source, to be detailed transaction data,quantitative and expressed in terms of units/hours⏹Includes customer orders and cash receipts.1.2Management accounting information for strategic planning and control☞Strategic management accounting is a form of management accounting in which emphasis is placed on information about factors which are external to the organisation, as well as non-financial and internally-generated information.⏹External orientation: competitive advantage is relative; customer determination⏹Future orientation: forward- and outward looking; concern with values.⏹Goal congruence: translates the consequences of different strategies into a commonaccounting language for comparison; relates business operations to financial performance.1.3Planning and control at strategic and operational levels☞Linking strategy and operations, if not: unrealistic plans, inconsistent goals, poor communication, inadequate performance measurement.1.3.1Strategic control systems☞Formal systems of strategic control:⏹strategy review;⏹identify milestones of performance( outline critical success factors, short-term stepstowards long-term goals, enables managers to monitor actions)⏹Set target achievement levels (targets must be reasonably precise, suggest strategiesand tactics, relative to competition)⏹Formal monitoring of the strategic process⏹Reward.☞Desired features of strategic performance measures⏹Focus on what matters in the long term⏹Identify and communicate drivers of success⏹Support organisational learning⏹Provide a basis for reward⏹Measurable; meaningful; acceptable;⏹Described by strategy and relevant to it⏹Consistently measured⏹Re-evaluated regularly1.4Benchmarking1.4.1Types of benchmarking☞Internal benchmarking: easy; no innovative or best-practice.☞Industry benchmarking:⏹Competitor benchmarking: difficult to obtain information⏹Non-competitor benchmarking: motivate☞Functional benchmarking: find new, innovative ways to create competitive advantage1.4.2Stages of benchmarking☞Set objectives and determine the area to benchmark☞Establish key performance measures.☞Select organizations to study☞Measure own and others performance☞Compare performance☞Design and implement improvement prgoramme☞Monitor improvements1.4.3Reasons for benchmarking☞Assess current strategic position☞Assess generic competitive strategy☞Spur to innovation☞Setting objectives and targets☞Cross comparisons☞Implementing change☞Identifies the process to improve☞Helps with cost reduction, or identifying areas where improvement is required☞Improves the effectiveness of operations☞Delivers services to a defined standard☞Provide early warning of competitive disadvantage1.4.4Disadvantages of benchmarking☞Implies there is one best way of doing business☞Yesterday’s solution to tomorrow’s problem☞Catching-up exercise rather than the development of anything distinctive☞Depends on accurate information about comparator companies☞Potential negative side effects of ‘what gets measured gets done’.2Performance management and control of the organization2.1Strengths and weaknesses of alternative budget models2.1.1Incremental budgeting☞Is the traditional approach to setting a budget and involves basing next year’s budget on the current year’s results plus an extra amount for estimated growth of inflation next year. ☞Strengths: easy to prepare; can be flexed to actual levels to provide more meaningful control information☞Weaknesses: does not take account of alternative options; does not look for ways of improving performance; only works if current operations are as effective, efficient and economical as they can be; encourage slack in the budget setting process.2.1.2Zero based budgeting☞Preparing a budget for each cost centre from scratch.☞Strengths:⏹Provides a budgeting and planning tool for management that responds to changes inthe business environment.⏹Requires the organization to look very closely at its cost behavior patterns, andimproves understanding of cost-behaviour patterns.⏹Should help identify inefficient or obsolete processes, and thereby also help reducecosts.⏹Results in a more efficient allocation of resources⏹Be particularly useful in not-for-profit organizations which have a focus on achievingvalue for money.☞Weaknesses:⏹Requires a lot of management time and effort⏹Requires training in the use of ZBB techniques so that these are applied properly⏹Questioning current practices and processes can be seen as threatening2.1.3Rolling budgets☞Continuously updated by adding a further period when the earliest period has expired.☞Strengths:⏹Reduce the uncertainty of budgeting for business operating in an unstableenvironment. It is easier to predict what will happen in the short-term.⏹Most suitable form of budgeting for organizations in uncertain environments, wherefuture activity levels, costs or revenues cannot be accurately foreseen.⏹Planning and control is based on a more recent plan which is likely to be morerealistic an more relevant than a fixed annual budget drawn up several months ago.⏹The process of updating the budget means that managers identify current changes( and so can respond to these changes more quickly)⏹More realistic targets provide a better basis on which to appraise managers’performance⏹Realistic budgets are likely to have a better motivational effect on managers.☞Weaknesses:⏹Require time, effort and money to prepare and keep updating. If managers spend toolong preparing/revising budgets, they will have less time to control and manage actual results⏹Managers may not see the value in the continuous updating of budgets⏹May be demotivating if targets are constantly changing⏹It may not be necessary to update budgets so regularly in a stable operatingenvironment.2.1.4Flexible budgets☞Recognizing the potential uncertainty, budgets designed to adjust costs levels according to changes in the actual levels of activity and output.☞Strengths:⏹Finding out well in advance the costs of idle time and so on if the output falls belowbudget.⏹Being able to plan for the alternative use of spare capacity if output falls short ofbudget☞Weaknesses:⏹As many errors in modern industry are fixed costs, the value of flexible budgets as aplanning tool are limited.⏹Where there is a high degree of stability, the administrative effort in flexiblebudgeting produces little extra benefit. Fixed budgets can be perfectly adequate in these circumstances.2.1.5Activity based budgeting☞Involves defining the activities that underlie the financial figures in each function and usingthe level of activity to decide how much resources should be allocated, how well it is being managed and to explain variance from budget.☞Strengths:⏹Ensures that the organisation’s overall strategy and any changes to that strategy willbe taken into account.⏹Identifies critical success factors which are activities that a business must perform wellif it is to succeed⏹Recognizes that activities drive costs; so encourages a focus on controlling andmanaging cost drivers rather than just the costs⏹Concentrate on the whole activities so that there is more likelihood of getting it rightfirst time.☞Weaknesses:⏹Requires time and effort to prepare so suited to a more complex organization withmultiple cost drivers.⏹May be difficult to identify clear individual responsibilities for activities⏹Only suitable for organization which have adopted an activity-based costing system⏹ABBs are not suitable for all organization, especially with significant proportions offixed overheads.2.1.6The future of budgeting☞Criticisms of traditional budgeting⏹Time consuming and costly⏹Major barrier to responsiveness, flexibility and change⏹Adds little value given the amount of management time required⏹Rarely strategically focused⏹Makes people feel undervalued⏹Reinforces department barriers rather than encouraging knowledge sharing⏹Based on unsupported assumptions and guesswork as opposed to sound,well-constructed performance data⏹Development and updated infrequently2.2Budgeting in not-for-profit organizations☞Special issues: the budget process inevitably has considerable influence on organizational processes, and represents the financial expression of policies resulting from politically motivated goals and objectives. The reality of life for many public sector managers is an subjected to(受---支配) growing competition.⏹Be prevented from borrowing funds⏹Prevent the transfer of funds from one budget head to another without compliancewith various rules and regulations⏹Plan one financial year.⏹Incremental budgeting and the bid system are widely used.2.3Evaluating the organisation’s move beyond budgeting2.3.1Conventional budgeting in a changing environment☞Weaknesses of traditional budgets:⏹Adds little value, requires far too much valuable management time⏹Too heavy a reliance on the ‘agreed’ budget has an adverse impact on managementbehavior, which can become dysfunctional(功能失调的) with regard to(关于) the objectives of the organization as a whole⏹The use of budgeting as a base for communicating corporate goals, is contrary to theoriginal purpose of budgeting as a financial control mechanism⏹Most budgets are not based on a rational, causal(因果关系的) model of resourceconsumption, but are often the result of protracted internal bargaining processes.⏹Conformance to budget is not seen as compatible with a drive towards continuousimprovement⏹Traditional budgeting processes have insufficient external focus.2.3.2The beyond budgeting model☞Rolling budgets focus management attention on current and likely future realities within the organizational context, it is seen as an attempt to keep ahead of change, or strictly speaking to be more in control of the response to the challenges facing the organization. ☞Benefits:⏹Creates and fosters a performance climate based on competitive success. Managerialfocus shifts from beating other managers for a slice(部分) of resources to beating the competition.⏹It motivates properly by giving them challenges, responsibilities and clear values asguidelines. Rewards are team-based⏹It empowers operational managers to act by removing resource constraints. Speedingup the response to environmental threats and enabling quick exploitation of new opportunities.⏹It devolves performance responsibilities to operational management who are closer tothe action.⏹It establishes customer-orientated teams that are accountable for profitable customeroutcomes.⏹Creates transparent and open information systems throughout the organization,provides fast, open and distributed information to facilitate control at all levels.3Business structure, IT development and other environmental and ethical issues3.1Business structure and information needs3.1.1Functional departmentation☞Information characteristics and needs: information flows vertically; functions tend to be isolated☞Implications for performance management⏹Structure is based on work specialism⏹Economies of scale⏹Does not reflect the actual business processes by which values is created⏹Hard to identify where profits and losses are made on individual products or inindividual markets⏹People do not have an understanding of how the whole business works⏹Problems of co-ordinating the work of different specialisms.3.1.2The divisional form☞Information characteristics and needs⏹Divisionalisation is the division of a business into autonomous regions⏹Communication between divisions and head office is restricted, formal and related toperformance standards⏹Headquarters management influence prices and therefore profitability when it setstransfer prices between divisions.⏹Divisionalisation is a function of organisation size, in numbers and in product-marketactivities.☞Implications for performance management⏹Divisional management should be free to use their authority to do what they think isright, but must be held accountable to head office⏹ A division must be large enough to support the quantity and quality of managementit needs⏹Each division must have a potential for growth in its own area of operations⏹There should be scope and challenge in the job for the management of the division☞Advantages:⏹Focuses the attention of subordinate(下级) management on business performanceand results⏹Management by objectives can be applied more easily⏹Gives more authority to junior managers, more senior positions⏹Tests junior managers in independent command early in their careers and at areasonably low level in the management hierarchy.⏹Provides an organisation structure which reduces the number of levels ofmanagement.☞Problems:⏹Partly insulated from shareholders and capital markets⏹The economic advantages it offers over independent organisations ‘reflectfundamental inefficiencies in capital markets’⏹The divisions are more bureaucratic than they would be as independent corporation⏹Headquarters management usurp divisional profits by management charges,cross-subsidies, unfair transfer pricing systems.⏹Sometime, it is impossible to identify completely independent products or markets⏹Divisionalisation is only possible at a fairly senior management level⏹Halfway house(中途地点)⏹Divisional performance is not directly assessed by the market⏹Conglomerate diversification3.1.3Network organisations☞Information characteristics and needs: achieve innovative response in a changingcircumstances; communication tends to be lateral(侧面的), information and advice are given rather than instructions(指令) and decisions.☞Virtual teams: share information and tasks; make joint decision; fulfil the collaborative function of a team)☞Implications for performance management⏹Staffing: shamrock organisation⏹Leasing of facilities such as IT, machinery and accommodation(住房)⏹Production itself might be outsourced⏹Interdependence of organisations☞Benefits: cost reduction; increased market penetration; experience curve effects.3.2Business process re-engineering3.2.1Business processes and the technological interdependence betweendepartments☞Pooled interdependence(联营式相互依赖): each department works independently to the others, subjects to achieve the overall goals☞Sequential interdependence(序列式相互依存): a sequence with a start and end point.Management effort is required to ensure than the transfer of resources between departments is smooth.☞Reciprocal interdependence(互惠式相互依存): a number of departments acquire inputs from and offer outputs to each other.3.2.2Key characteristics of organisations which have adopted BPR☞Work units change from functional departments to process teams, which replace the old functional structure☞Jobs change. Job enlargement and job enrichment☞People’s roles change. Make decisions relevant to the process☞Performance measures concentrate on results rather than activities.☞Organisation structures change from hierarchical to flat3.3Business integration3.3.1Mckinsey 7S model☞Hard elements of business behaviour⏹Structure: formal division of tasks; hierarchy of authority⏹Strategy: plans to outperform胜过its competitors.⏹Systems: technical systems of accounting, personnel, management information☞‘soft’ elements⏹Style: shared assumptions, ways of working, attitudes and beliefs⏹Shared values: guiding beliefs of people in the organisation as to why it exists⏹Staff: people⏹Skills: those things the organisation does well3.3.2Teamwork and empowerment☞Aspects of teams:⏹Work organisation: combine the skills of different individuals and avoid complexcommunication⏹Control: control the behaviour and performance of individuals, resolve conflict⏹Knowledge generation: generate ideas⏹Decision making: investigate new developments, evaluate new decisions☞Multi-disciplinary teams:⏹Increases workers‘ awareness of their overall objectives and targets⏹Aids co-ordination⏹Helps to generate solutions to problems, suggestions for improvements☞Changes to management accounting systems⏹Source of input information: sources of data, methods used to record data⏹Processing involved: cost/benefit calculation⏹Output required: level of detail and accuracy of output, timescales involved⏹Response required:⏹When the output is required:3.4Information needs of manufacturing and service businesses3.4.1Information needs of manufacturing businesses☞Cost behaviour:⏹Planning: standard costs, actual costs compared with⏹Decision making: estimates of future costs to assess the likely profitability of a product⏹Control: monitor total cost information☞Quality: the customer satisfaction is built into the manufacturing system and its outputs☞Time: production bottlenecks, delivery times, deadlines, machine speed☞Innovation: product development, speed to market, new process. Experience curve, economies of scale, technological improvements.☞Valuation:☞Strategic, tactical and operational information⏹Strategic: future demand estimates, new product development plans, competitoranalysis⏹Tactical: variance analysis, departmental accounts, inventory turnover⏹Operational: production reject rates, materials and labour used, inventory levels3.4.2Service businesses☞Characteristics distinguish from manufacturing:⏹Intangibility: no substance⏹Inseparability/simultaneity: created at the same time as they are consumed⏹Variability/heterogeneity异质性: problem of maintaining consistency in the standardof output⏹Perishability非持久性:⏹No transfer of ownership:☞Strategic, tactical and operational information⏹Strategic: forecast sales growth and market share, profitability, capital structure⏹Tactical: resource utilisation, customer satisfaction rating⏹Operational: staff timesheets, customer waiting time, individual customer feedback3.5Developing management accounting systems3.5.1Setting up a management accounting system☞The output required: identify the information needs of managers☞When the output is required:☞The sources of input information: the output required dictate the input made3.6Stakeholders’ goals and objectives3.6.1The stakeholder view☞Organisations are rarely controlled effectively by shareholders☞Large corporations can manipulate markets. Social responsibility☞Business receive a lot of government support☞Strategic decisions by businesses always have wider social consequences.3.6.2Stakeholder theory☞Strong stakeholder view: each stakeholder in the business has a legitimate claim on management attention. Management’s job is to balance stakeholder demands:⏹Managers who are accountable to everyone are accountable to none⏹Danger of the managers favour their own interests⏹Confuses a stakeholder’s interest in a firm with a person citizenship of a state⏹People have interest, but this does not give them rights.3.7Ethics and organisation3.7.1Short-term shareholder interest(laissez-faire自由主义stance)☞Accept a duty of obedience to the demands of the law, but would not undertake to comply with any less substantial rules of conduct.3.7.2Long-term shareholder interest (enlightened self-interest开明自利)☞The organisation’s corporate image may be enhanced by an assumption of wider responsibilities.☞The responsible exercise of corporate power may prevent a built-up of social and political pressure for legal regulation.3.7.3Multiple stakeholder obligations☞Accept the legitimacy of the expectations of stakeholders other than shareholders. It is important to take account of the views of stakeholders with interests relating to social and environmental matters.☞Shape of society: society is more important than financial and other stakeholder interests.3.7.4Ethical dilemmas☞Extortion: foreign officials have been known to threaten companies with the complete closure of their local operations unless suitable payments are made☞Bribery: payments for service to which a company is not legally entitled☞Grease money: cash payments to the right people to oil the machinery of bureaucracy.☞Gifts: are regard as an essential part of civilised negotiation.4Changing business environment and external factors4.1The changing business environment4.1.1The changing competitive environment☞Manufacturing organisations:⏹Before 1970s, domestic markets because of barriers of communication andgeographical distance, few efforts to maximise efficiency and improve management practices.⏹After 1970s, overseas competitors, global networks for acquiring raw materials anddistributing high-quality, low-priced goods.☞Service organisations:⏹Prior to the 1980s: service organisations were government-owned monopolies, wereprotected by a highly-regulated, non-competitive environment.⏹After 1980s: privatisation of government-owned monopolies and deregulation, intensecompetition, led to the requirement of cost management and management accounting information systems.☞Changing product life cycles: competitive environment, technological innovation, increasingly discriminating and sophisticated customer demands.☞Changing customer requirements: Cost efficiency, quality (TQM), time (speedier response to customer requests), innovation☞New management approaches: continuous improvement, employee empowerment; total value-chain analysis☞Advanced manufacturing technology(AMT): encompasses automatic production technology, computer-aided design and manufacturing, flexible manufacturing systems and a wide array of innovative computer equipment.4.1.2The limitation of traditional management accounting techniques in achanging environment☞Cost reporting: costs are generally on a functional basis, the things that businesses do are “process es’ that cut across functional boundaries☞Absorption costing(归纳成本计算法)☞Standard costing: ignores the impact of changing cost structures; doesn’t provide any incentive to try to reduce costs further, is inconsistent with the philosophy of continuous improvement.☞Short-term financial measures: narrowly focused☞Cost accounting methods: trace raw materials to various production stages via WIP. With JIT systems, near-zero inventories, very low batch sizes, cost accounting and recording systems are greatly simplified.☞Performance measures: product the wrong type of response☞Timing: cost of a product is substantially determined when it is being designed, however, management accountants continue to direct their efforts to the production stage.☞Controllability: only a small proportion of ‘direct costs’are genuinely controllable in the short term.☞Customers: many costs are driven by customers, but conventional cost accounting does not recognise this.☞The solution: changes are taking place in management accounting in order to meet the challenge of modern developments.4.2Risk and uncertainty4.2.1Types of risk and uncertainty☞Physical: earthquake, fire, blooding, and equipment breakdown. Climatic changes: global warming, drought;☞Economic: economic environment turn out to be wrong☞Business: lowering of entry barriers; changes in customer/supplier industries; new competitors and factors internal to the firm; management misunderstanding of core competences; volatile cash flows; uncertain returns☞Product life cycle:☞Political: nationalisation, sanctions, civil war, political instability☞Financial:4.2.2Accounting for risk☞Quantify the risk:⏹Rule of thumb methods: express a range of values from worst possible result to bestpossible result with a best estimate lying between these two extremes.⏹Basic probability theory: expresses the likelihood of a forecast result occurring⏹Dispersion or spread values with different possible outcomes: standard deviation.4.2.3Basic probability theory and expected valuesEV=ΣpxP=the probability of an outcome occurringX=the value(profit or loss) of that outcome4.2.4Risk preference☞Risk seeker: is a decision maker who is interested trying to secure the best outcomes no matter how small the chance they may occur☞Risk neutral: a decision maker is concerned with what will be the most likely outcome☞Risk averse: a decision maker acts on the assumption that the worst outcome might occur ☞Risk appetite is the amount of risk an organisation is willing to take on or is prepared to accept in pursuing its strategic objectives.4.2.5Decision rules☞Maximin decision rule: select the alternative that offers the least unattractive worst outcome. Maximise the minimum achievable profit.⏹Problems: risk-averse approach, lead to defensive and conservative, without takinginto account opportunities for maximising profits⏹Ignores the probability of each different outcome taking place☞Maximax: looking for the best outcome. Maximise the maximum achievable profit⏹It ignores probabilities;⏹It is over-optimistic☞Minimax regret rule: minimise the regret from making the wrong decision. Regret is the opportunity lost through making the wrong decision⏹Regret for any combination of action and circumstances=profit for best action in shoescircumstances – profit for the action actually chosen in those circumstances4.3Factors to consider when assessing performance4.3.1Political factors☞Government policy; government plans for divestment(剥夺)/rationalisation; quotas, tariffs, restricting investment or competition; regulate on new products.☞Government policy affecting competition: purchasing decisions; regulations and control;policies to prevent the concentration of too much market share in the hands of one or two producers4.3.2Economic environment☞Gross domestic product: grown or fallen? Affection on the demand of goods/services☞Local economic trends: businesses rationalising or expanding? Rents increasing/falling?The direction of house prices moving? Labour rates☞Inflation: too high to making a plan, uncertain of future financial returns; too low to depressing consumer demand; encouraging investment in domestic industries; high rate leading employees to demand higher money wages to compensate for a fall in the value of their wages☞Interest rates: affect consumer confidence and liquidity, demand; cost of borrowing increasing, reducing profitability;☞Exchange rates: impact on the cost of overseas imports; prices affect overseas customers ☞Government fiscal policy: increasing/decreasing demands; corporate tax policy affecting on the organisation; sales tax(VAT) affecting demand.☞Government spending:☞Business cycle: economic booming or in recession; counter-cyclical industry; the forecast state of the economic4.3.3Funding☞Reasons for being reluctant to obtain further debt finance:⏹Fear the company can’t service the debt, make the required capital and interestpayments on time⏹Can’t use the tax shield, to obtain any tax benefit from interest payments⏹Lacks the asset base to generate additional cash if needed or provide sufficientsecurity⏹Maintain access to the capital markets on good terms.4.3.4Socio-cultural factors☞Class: different social classes have different values。
交通行业术语（中英文对照）Stop-line ----- 停车线A con gested link ---- 阻塞路段Weighti ng factor ----- 权重因子Con troller --- 控制器Emissio ns Model ---- 排气仿真the traffic pattern ----- 交通方式Con troller --- 信号机Amber ----- 黄灯Start-up delay ---- 启动延误Lost time ----- 损失时间Off-peak——非高峰期The morni ng peak -- 早高峰Pedestria n crossin ——人行横道Coord in ated con trol systems——协调控制系统On-I ine ---- 实时Two-way ----- 双向交通Absolute Offset ----- 绝对相位差Overlapp ing Phase——搭接相位Critical Phase ----- 关键相位Cha nge Interval --- 绿灯间隔时间Arterial In tersection Con trol 干线信号协调控制Fixed-time Con trol ----- 固定式信号控制Real-time Adaptive Traffic Con trol ---- 实时自适应信号控制Green Ratio ---- 绿信比Through movemen ----- 直行车流Congestion ----- 阻塞，拥挤The perce ntage congestion——阻塞率The degree of saturation——饱和度The effective gree n time --- 有效绿灯时间The maximum queue value——最大排队长度Flow Profiles ------ 车流图示Double cycli ng ----- 双周期Si ngle cycli ng --- 单周期Peak高峰期The eve ning peak periods——晚高峰Siemens --- 西门子Pelican ---- 人行横道Fixed time plans ---- 固定配时方案On e-way traffic ---- 单向交通Green Ratio ---- 绿信比Relative Offset ----- 相对相位差Non-o verlapp ing Phase——非搭接相位Saturatio n Flow Rate -- 饱和流率Isolated In tersecti on Contro -- 单点信号控制（点控）Area-wide Con trol ---- 区域信号协调控制Vehicle Actuated （\A）-- 感应式信号控制The Mi nimum Green Time ---- 最小绿灯时间Unit Exte nsion Time --- 单位绿灯延长时间The Maximum Green Time ---- 最大绿灯时间Oppos ing traffic --- 对向交通（车流）Actuati on ---- Con trol ----- 感应控制方式Pre-timed Control ------ 定周期控制方式Remote Contro ----- 有缆线控方式Self —I nductfa ns --- 环形线圈检测器Signal ----- s pacin -------- 信号间距Though-traffic lane ----- 直行车道Inbound ---- 正向Outbound ---- 反向第一章交通工程--- Traffic Engin eeri ng运输工程--- Tran sportati on Engin eeri ng航空交通--- Air Tran sportati on水上交通--- Water Tran sportati on管道交通--- Pipeli ne Tran sportati on交通系统--- Traffic System交通特性--- Traffic Characteristics人的特性--- Huma n Characteristics车辆特性--- Vehicular Characteristics交通流特性--- Traffic Flow Characteristics道路特性--- Roadway Characteristics交通调查--- Traffic Survey交通流理论--- Traffic Flow Theory交通管理--- Traffic Man ageme nt交通环境保护---- T raffic En vir onment Protecti on 交通设计--- Traffic Desig n交通统计学--- Traffic Statistics交通心理学--- Traffic Psychology汽车力学--- Automobile Mecha nics交通经济学--- Traffic Econo mics汽车工程--- Automobile Engin eeri ng人类工程--- Huma n Engin eeri ng环境工程--- En vir onment Engin eeri ng自动控制--- Automatic Con trol电子计算机Electric Computer第一章公共汽车一Bus无轨电车Trolley Bus有轨电车Tram Car大客车Coach小轿车Seda n载货卡车Truck拖挂车Trailer平板车Flat-bed Truck动力特性一Drivi ng Force Characteristics 牵引力Tractive Force空气阻力Air Resista nee滚动阻力Rolli ng Resista nee坡度阻力Grade Resista nee加速阻力Accelerati on Resista nee附着力一一 Adhesive Force汽车的制动力Braki ng of Motor Vehicle 自行车流特性Bicycle flow Characteristics驾驶员特性Driver Characteristics刺激Stimulation感觉--- Sense判断--- Judgme nt行动--- Action视觉--- Visual Sense听觉--- Heari ng Sense嗅觉--- Se nse of Smell味觉--- Sense of Touch视觉特性--- Visual Characteristics视力--- Visi on视野--- Field of Visio n色彩感觉--- Color Sense眩目时的视力--- Glare Visio n视力恢复--- Retur n Time of Visio n动视力--- Visual in Motion亮度--- Luminance照度--- Luminance反应特性--- Reactive Characteristics刺激信息--- Stimula nt In formati on驾驶员疲劳与兴奋---- Drivi ng Fati ng and Excitability交通量--- Traffic Volume地点车速Spot Speed瞬时车速In sta ntan eous Speed时间平均车速Time mean Speed空间平均车速Space mean speed车头时距Time headway车头间距一一Space headway。
统计学方法英语As an essential tool in data analysis, statistical methods play a crucial role in various fields such as economics, psychology, biology, and social sciences. 统计学方法作为数据分析中的重要工具，在经济学、心理学、生物学和社会科学等领域起着至关重要的作用。
By utilizing statistical techniques, researchers are able to draw meaningful conclusions from data, identify trends and patterns, and make informed decisions. 通过利用统计技术，研究人员能够从数据中得出有意义的结论，识别趋势和模式，并做出明智的决策。
Statistical methods provide a framework for organizing, analyzing, and interpreting data to extract valuable insights that can inform decision-making processes. 统计方法提供了一个框架，用于组织、分析和解释数据，从而提取有价值的洞察，可以指导决策过程。
One of the key advantages of statistical methods is their ability to quantify uncertainty and variability in data. 统计方法的一个关键优势是其能力量化数据中的不确定性和变异性。
By using probability theory and hypothesis testing, statisticians can assess the reliability of their findings and make valid inferences about populations based on sample data. 通过使用概率论和假设检验，统计学家可以评估其发现的可靠性，并根据样本数据对总体进行有效推断。
质量工程师英语词汇汇总1. PDCA : : Plan、Do、Check、Action 策划、实施、检查、处置2. PPAP : Production PartApproval Process 生产件批准程序3. APQP : Advaneed ProductQuality Planning 产品质量先期策划4. FMEA : Potential FailureMode and Effects Analysis 潜在失效模式及后果分析5.SPC : Statistical ProcessControl 统计过程控制6. MSA : Measurement SystemAnalysis 测量系统控制7. CP : Control Plan 控制计划8. QSA : Quality SystemAssessment 质量体系评定9. PPM : Parts Per Million 每百万零件不合格数10. QM : : Quality Manua 质量手册11. QP : : Quality Procedure 质量程序文件/Quality Planning 质量策划/QualityPlan质量计划12. CMK :机器能力指数13. CPK :过程能力指数14. CAD : : Computer-AidedDesign 计算机辅助能力设计15.OEE : Overall Equipment Effectiveness 设备总效率精选资料16.QFD : Quality FunctionDeployment 质量功能展开功能展开17. FIF0: : First in, First out 先进先出先进先出18. COPS : : Customer OrientedProcesses 顾客导向过程顾客导向过程19. TCQ: : Time 、Cost 、Quality 时间、成本、质量时间、成本、质量 20. MPS : Management Processes 管理性过程管理性过程21.SPS : Support Processes 支持性过程支持性过程22. TQM : Total QualityManagement 全面质量管理全面质量管理23. PQA : Product QualityAssuranee产品质量保证（免检）产品质量保证（免检）24. QP-QC-QI :质量改进质量三步曲，质量计划—质量控制—质量改进25. QAF : Quality AssuranceFile 质量保证文件质量保证文件26. QAP : Quality AssurancePlan 质量保证计划质量保证计划27. PFC : Process Flow Chart 过程流程图过程流程图 28. QMS : Quality ManagementSystems 质量管理体系质量管理体系29. JIT : Just In Time准时（交货）准时（交货） 30. ERP : EnterpriseRequirement Planning企业需求计划企业需求计划 31. QC : Quality Control 质量控制质量控制32. QA : Quality Audit质量审核质量审核质量审核 /QalityAssuranee 质量保证质量保证33.IQC : In Come QualityControl进货质量控制进货质量控制过程质量控制34.IPQC : In Process QualityControl 过程质量控制成品质量控制35.FQC : Final QualityControl 成品质量控制出货质量控制36.OQC : Out Quality Control 出货质量控制人、机、料、 37.4M1E : Man、Machine、Material、Method、Environment 人、机、料、法、环法、环做什么 / 谁做/ 时38.5W1H : Why、What、Who、When、Where、How 为何/ 做什么如何做间/地点/如何做整理、整顿、清39.6S : Seiri、Seiton、Seiso、Seiketsu、Shitsuke 、Safety 整理、整顿、清扫、清洁、素养、安全扫、清洁、素养、安全（三种）可记录工伤值40. TRI值：Total Record Injury （三种）可记录工伤值41.SMART :精明原则，SpecificMeasurable Achievable Result OrientedTimed （具体的描述、可以测量的、可以通过努力实现的、有结果导向性的、有时间性的）间性的）----------- 企业常用英文缩写----------- 管理1.5S : 5S 管理2. ABC :作业制成本制度(Activity-BasedCosting )3. ABB :实施作业制预算制度(Activity-BasedBudgeting )4. ABM :作业制成本管理(Activity-BaseManagement )5. APS :先进规画与排程系统(AdvancedPlanning and Scheduling )6. ASP :应用程序服务供货商(ApplicationService Provider )7. ATP :可承诺量(Available ToPromise )8. AVL :认可的供货商清单(ApprovedVendor List )9. BOM :物料清单(Bill OfMaterial )10. BPR :企业流程再造(Bus in essProcess Ree ngi neering )11. BSC :平衡记分卡(BalancedScoreCard )12. BTF :计划生产(Build ToForecast )13. BTO :订单生产(Build To Order )14. CPM :要径法(Critical PathMethod )15. CPM :每一百万个使用者会有几次抱怨(Complaintper Million )16. CRM :客户关系管理(CustomerRelationship Management )17. CRP :产能需求规划(CapacityRequirements Planning )18. CTO :客制化生产(Con figurati on To Order )19. DBR :限制驱导式排程法(Drum-Buffer-Rope )20. DMT :成熟度验证(Desig nM aturi ng Testi ng )21. DVT :设计验证(Desig nV erificati on Testi ng )22. DRP :运销资源计划(DistributionResource Planning )23. DSS :决策支持系统(DecisionSupport System )24. EC :设计变更/工程变更(EngineerChange )25. EC :电子商务(ElectronicCommerce )26. ECRN :原件规格更改通知(EngineerChange Request Notice )27. EDI :电子数据交换(ElectronieData Interchange )28. EIS :主管决策系统(Executivelnformation System )29. EMC :电磁相容(ElectricMagnetic Capability )30. EOQ :基本经济订购量(EconomicOrder Quantity )31. ERP :企业资源规划(EnterpriseResource Planning )32. FAE :应用工程师(FieldApplication Engineer )33. FCST :预估(Forecast)34. FMS :弹性制造系统(FlexibleManufacture System )35. FQC :成品质量管理(Finish orFinal Quality Control )36.IPQC:制程质量管理(In-ProcessQuality Control )37.IQC :进料质量管理(In comi ngQuality Co ntrol )38.ISO :国际标准组织(InternationalOrganization for Standardization )39.ISAR :首批样品认可(InitialSample Approval Request )40. JIT :实时管理(Just In Time )41. KM :知识管理(KnowledgeManagement )42. L4L :逐批订购法(Lot-for-Lot )43. LTC :最小总成本法(Least TotalCost )44. LUC :最小单位成本(Least UnitCost )45. MES :制造执行系统(ManufacturingExecution System )46. MO :制令(Manufacture Order )47. MPS :主生产排程(MasterProduction Schedule )48. MRO :请修(购)单(MaintenanceRepair Operation )49. MRP :物料需求规划(MaterialRequirement Planning )50. MRPII :制造资源计划(ManufacturingResource Planning )更改预估量的通知 Notice forChanging Forecast51. NFCF :更改预估量的通知52.OEM :委托代工(OriginalEquipment Manufacture )53.ODM :委托设计与制造(OriginalDesign & Manufacture )54.OLAP :在线分析处理(On-LineAnalytical Processing )55.OLTP :在线交易处理(On-LineTransaction Processing )56.OPT :最佳生产技术(OptimizedProduction Techno logy )57.OQC :出货质量管理(Out-goingQuality Control )58. PDCA : PDCA 管理循环(Plan-Do-Check-Action )59. PDM :产品数据管理系统(ProductData Management )60. PERT :计划评核术(ProgramEvaluation and Review Technique )61. P0 :订单(Purchase Order )62. POH :预估在手量(Product。
「中國人個性測量表」在西方樣本的初步研究香港中文大學心理學系張樹輝發表於:「泛華心理學研究的切磋與交流」第四屆華人心理學家學術研討會暨第六屆華人心理與行為科際學術研討會2002年11月9日至11日台灣台北中央研究所本研究得到香港特區政府研究資助委員會(Earmarked Grant Project #2120149) 及香港中文大學 (Direct Grant #2020662) 資助。
本文所採用的中國人個性測量表(CPAI)是香港中文大學心理學系及中國科學院心理研究所之合作成果，作者包括張妙清教授、梁覺教授、張建新教授、宋維真教授、及張建平教授。
本文部份結果取材自另一篇論文，由張妙清、張樹輝、梁覺、Colleen Ward、及梁天樂合撰。
該論文將對本研究有更詳細的討論。
特此鳴謝Prof. Colleen Ward在新加坡收集華人樣本，及梁天樂教授在美國收集的白人樣本。
本論文主要對「中國人個性測量表」（The Chinese Personality Assessment Inventory，簡稱CPAI）在西方樣本的因素結構（Factor Structure）作初步探討。
CPAI是張妙清等（1996）根據經驗歸納法，從華人文化的角度出發而編訂的一套具中華文化相關性的本土化人格量表。
在2001年張妙清等發現，把CPAI與西方著名的人格量表NEO-PI-R進行聯合因素分析（Joint Factor Analysis），人際關係向度是獨立於NEO-PI-R的五個向度。
其他的研究亦顯示人際關係向度在華人社會中起一定的作用。
Ho（2001）認為，人在社會中的行為並不獨立於其他人的影響，而早期的西方心理學亦有關於人際關係的理論（例如Sullivan，1953、Wiggins，1979）。
因此作為中華文化的其中一個人格心理學角度，值得研究本土化華人量表CPAI在西方文化的樣本的因素結構。
本論文包括兩個研究。
第一個研究主要是有關英語版的CPAI的編訂及初步驗證。
Network impacts of a road capacity reduction:Empirical analysisand model predictionsDavid Watling a ,⇑,David Milne a ,Stephen Clark baInstitute for Transport Studies,University of Leeds,Woodhouse Lane,Leeds LS29JT,UK b Leeds City Council,Leonardo Building,2Rossington Street,Leeds LS28HD,UKa r t i c l e i n f o Article history:Received 24May 2010Received in revised form 15July 2011Accepted 7September 2011Keywords:Traffic assignment Network models Equilibrium Route choice Day-to-day variabilitya b s t r a c tIn spite of their widespread use in policy design and evaluation,relatively little evidencehas been reported on how well traffic equilibrium models predict real network impacts.Here we present what we believe to be the first paper that together analyses the explicitimpacts on observed route choice of an actual network intervention and compares thiswith the before-and-after predictions of a network equilibrium model.The analysis isbased on the findings of an empirical study of the travel time and route choice impactsof a road capacity reduction.Time-stamped,partial licence plates were recorded across aseries of locations,over a period of days both with and without the capacity reduction,and the data were ‘matched’between locations using special-purpose statistical methods.Hypothesis tests were used to identify statistically significant changes in travel times androute choice,between the periods of days with and without the capacity reduction.A trafficnetwork equilibrium model was then independently applied to the same scenarios,and itspredictions compared with the empirical findings.From a comparison of route choice pat-terns,a particularly influential spatial effect was revealed of the parameter specifying therelative values of distance and travel time assumed in the generalised cost equations.When this parameter was ‘fitted’to the data without the capacity reduction,the networkmodel broadly predicted the route choice impacts of the capacity reduction,but with othervalues it was seen to perform poorly.The paper concludes by discussing the wider practicaland research implications of the study’s findings.Ó2011Elsevier Ltd.All rights reserved.1.IntroductionIt is well known that altering the localised characteristics of a road network,such as a planned change in road capacity,will tend to have both direct and indirect effects.The direct effects are imparted on the road itself,in terms of how it can deal with a given demand flow entering the link,with an impact on travel times to traverse the link at a given demand flow level.The indirect effects arise due to drivers changing their travel decisions,such as choice of route,in response to the altered travel times.There are many practical circumstances in which it is desirable to forecast these direct and indirect impacts in the context of a systematic change in road capacity.For example,in the case of proposed road widening or junction improvements,there is typically a need to justify econom-ically the required investment in terms of the benefits that will likely accrue.There are also several examples in which it is relevant to examine the impacts of road capacity reduction .For example,if one proposes to reallocate road space between alternative modes,such as increased bus and cycle lane provision or a pedestrianisation scheme,then typically a range of alternative designs exist which may differ in their ability to accommodate efficiently the new traffic and routing patterns.0965-8564/$-see front matter Ó2011Elsevier Ltd.All rights reserved.doi:10.1016/j.tra.2011.09.010⇑Corresponding author.Tel.:+441133436612;fax:+441133435334.E-mail address:d.p.watling@ (D.Watling).168 D.Watling et al./Transportation Research Part A46(2012)167–189Through mathematical modelling,the alternative designs may be tested in a simulated environment and the most efficient selected for implementation.Even after a particular design is selected,mathematical models may be used to adjust signal timings to optimise the use of the transport system.Road capacity may also be affected periodically by maintenance to essential services(e.g.water,electricity)or to the road itself,and often this can lead to restricted access over a period of days and weeks.In such cases,planning authorities may use modelling to devise suitable diversionary advice for drivers,and to plan any temporary changes to traffic signals or priorities.Berdica(2002)and Taylor et al.(2006)suggest more of a pro-ac-tive approach,proposing that models should be used to test networks for potential vulnerability,before any reduction mate-rialises,identifying links which if reduced in capacity over an extended period1would have a substantial impact on system performance.There are therefore practical requirements for a suitable network model of travel time and route choice impacts of capac-ity changes.The dominant method that has emerged for this purpose over the last decades is clearly the network equilibrium approach,as proposed by Beckmann et al.(1956)and developed in several directions since.The basis of using this approach is the proposition of what are believed to be‘rational’models of behaviour and other system components(e.g.link perfor-mance functions),with site-specific data used to tailor such models to particular case studies.Cross-sectional forecasts of network performance at specific road capacity states may then be made,such that at the time of any‘snapshot’forecast, drivers’route choices are in some kind of individually-optimum state.In this state,drivers cannot improve their route selec-tion by a unilateral change of route,at the snapshot travel time levels.The accepted practice is to‘validate’such models on a case-by-case basis,by ensuring that the model—when supplied with a particular set of parameters,input network data and input origin–destination demand data—reproduces current mea-sured mean link trafficflows and mean journey times,on a sample of links,to some degree of accuracy(see for example,the practical guidelines in TMIP(1997)and Highways Agency(2002)).This kind of aggregate level,cross-sectional validation to existing conditions persists across a range of network modelling paradigms,ranging from static and dynamic equilibrium (Florian and Nguyen,1976;Leonard and Tough,1979;Stephenson and Teply,1984;Matzoros et al.,1987;Janson et al., 1986;Janson,1991)to micro-simulation approaches(Laird et al.,1999;Ben-Akiva et al.,2000;Keenan,2005).While such an approach is plausible,it leaves many questions unanswered,and we would particularly highlight two: 1.The process of calibration and validation of a network equilibrium model may typically occur in a cycle.That is to say,having initially calibrated a model using the base data sources,if the subsequent validation reveals substantial discrep-ancies in some part of the network,it is then natural to adjust the model parameters(including perhaps even the OD matrix elements)until the model outputs better reflect the validation data.2In this process,then,we allow the adjustment of potentially a large number of network parameters and input data in order to replicate the validation data,yet these data themselves are highly aggregate,existing only at the link level.To be clear here,we are talking about a level of coarseness even greater than that in aggregate choice models,since we cannot even infer from link-level data the aggregate shares on alternative routes or OD movements.The question that arises is then:how many different combinations of parameters and input data values might lead to a similar link-level validation,and even if we knew the answer to this question,how might we choose between these alternative combinations?In practice,this issue is typically neglected,meaning that the‘valida-tion’is a rather weak test of the model.2.Since the data are cross-sectional in time(i.e.the aim is to reproduce current base conditions in equilibrium),then in spiteof the large efforts required in data collection,no empirical evidence is routinely collected regarding the model’s main purpose,namely its ability to predict changes in behaviour and network performance under changes to the network/ demand.This issue is exacerbated by the aggregation concerns in point1:the‘ambiguity’in choosing appropriate param-eter values to satisfy the aggregate,link-level,base validation strengthens the need to independently verify that,with the selected parameter values,the model responds reliably to changes.Although such problems–offitting equilibrium models to cross-sectional data–have long been recognised by practitioners and academics(see,e.g.,Goodwin,1998), the approach described above remains the state-of-practice.Having identified these two problems,how might we go about addressing them?One approach to thefirst problem would be to return to the underlying formulation of the network model,and instead require a model definition that permits analysis by statistical inference techniques(see for example,Nakayama et al.,2009).In this way,we may potentially exploit more information in the variability of the link-level data,with well-defined notions(such as maximum likelihood)allowing a systematic basis for selection between alternative parameter value combinations.However,this approach is still using rather limited data and it is natural not just to question the model but also the data that we use to calibrate and validate it.Yet this is not altogether straightforward to resolve.As Mahmassani and Jou(2000) remarked:‘A major difficulty...is obtaining observations of actual trip-maker behaviour,at the desired level of richness, simultaneously with measurements of prevailing conditions’.For this reason,several authors have turned to simulated gaming environments and/or stated preference techniques to elicit information on drivers’route choice behaviour(e.g. 1Clearly,more sporadic and less predictable reductions in capacity may also occur,such as in the case of breakdowns and accidents,and environmental factors such as severe weather,floods or landslides(see for example,Iida,1999),but the responses to such cases are outside the scope of the present paper. 2Some authors have suggested more systematic,bi-level type optimization processes for thisfitting process(e.g.Xu et al.,2004),but this has no material effect on the essential points above.D.Watling et al./Transportation Research Part A46(2012)167–189169 Mahmassani and Herman,1990;Iida et al.,1992;Khattak et al.,1993;Vaughn et al.,1995;Wardman et al.,1997;Jou,2001; Chen et al.,2001).This provides potentially rich information for calibrating complex behavioural models,but has the obvious limitation that it is based on imagined rather than real route choice situations.Aside from its common focus on hypothetical decision situations,this latter body of work also signifies a subtle change of emphasis in the treatment of the overall network calibration problem.Rather than viewing the network equilibrium calibra-tion process as a whole,the focus is on particular components of the model;in the cases above,the focus is on that compo-nent concerned with how drivers make route decisions.If we are prepared to make such a component-wise analysis,then certainly there exists abundant empirical evidence in the literature,with a history across a number of decades of research into issues such as the factors affecting drivers’route choice(e.g.Wachs,1967;Huchingson et al.,1977;Abu-Eisheh and Mannering,1987;Duffell and Kalombaris,1988;Antonisse et al.,1989;Bekhor et al.,2002;Liu et al.,2004),the nature of travel time variability(e.g.Smeed and Jeffcoate,1971;Montgomery and May,1987;May et al.,1989;McLeod et al., 1993),and the factors affecting trafficflow variability(Bonsall et al.,1984;Huff and Hanson,1986;Ribeiro,1994;Rakha and Van Aerde,1995;Fox et al.,1998).While these works provide useful evidence for the network equilibrium calibration problem,they do not provide a frame-work in which we can judge the overall‘fit’of a particular network model in the light of uncertainty,ambient variation and systematic changes in network attributes,be they related to the OD demand,the route choice process,travel times or the network data.Moreover,such data does nothing to address the second point made above,namely the question of how to validate the model forecasts under systematic changes to its inputs.The studies of Mannering et al.(1994)and Emmerink et al.(1996)are distinctive in this context in that they address some of the empirical concerns expressed in the context of travel information impacts,but their work stops at the stage of the empirical analysis,without a link being made to net-work prediction models.The focus of the present paper therefore is both to present thefindings of an empirical study and to link this empirical evidence to network forecasting models.More recently,Zhu et al.(2010)analysed several sources of data for evidence of the traffic and behavioural impacts of the I-35W bridge collapse in Minneapolis.Most pertinent to the present paper is their location-specific analysis of linkflows at 24locations;by computing the root mean square difference inflows between successive weeks,and comparing the trend for 2006with that for2007(the latter with the bridge collapse),they observed an apparent transient impact of the bridge col-lapse.They also showed there was no statistically-significant evidence of a difference in the pattern offlows in the period September–November2007(a period starting6weeks after the bridge collapse),when compared with the corresponding period in2006.They suggested that this was indicative of the length of a‘re-equilibration process’in a conceptual sense, though did not explicitly compare their empiricalfindings with those of a network equilibrium model.The structure of the remainder of the paper is as follows.In Section2we describe the process of selecting the real-life problem to analyse,together with the details and rationale behind the survey design.Following this,Section3describes the statistical techniques used to extract information on travel times and routing patterns from the survey data.Statistical inference is then considered in Section4,with the aim of detecting statistically significant explanatory factors.In Section5 comparisons are made between the observed network data and those predicted by a network equilibrium model.Finally,in Section6the conclusions of the study are highlighted,and recommendations made for both practice and future research.2.Experimental designThe ultimate objective of the study was to compare actual data with the output of a traffic network equilibrium model, specifically in terms of how well the equilibrium model was able to correctly forecast the impact of a systematic change ap-plied to the network.While a wealth of surveillance data on linkflows and travel times is routinely collected by many local and national agencies,we did not believe that such data would be sufficiently informative for our purposes.The reason is that while such data can often be disaggregated down to small time step resolutions,the data remains aggregate in terms of what it informs about driver response,since it does not provide the opportunity to explicitly trace vehicles(even in aggre-gate form)across more than one location.This has the effect that observed differences in linkflows might be attributed to many potential causes:it is especially difficult to separate out,say,ambient daily variation in the trip demand matrix from systematic changes in route choice,since both may give rise to similar impacts on observed linkflow patterns across re-corded sites.While methods do exist for reconstructing OD and network route patterns from observed link data(e.g.Yang et al.,1994),these are typically based on the premise of a valid network equilibrium model:in this case then,the data would not be able to give independent information on the validity of the network equilibrium approach.For these reasons it was decided to design and implement a purpose-built survey.However,it would not be efficient to extensively monitor a network in order to wait for something to happen,and therefore we required advance notification of some planned intervention.For this reason we chose to study the impact of urban maintenance work affecting the roads,which UK local government authorities organise on an annual basis as part of their‘Local Transport Plan’.The city council of York,a historic city in the north of England,agreed to inform us of their plans and to assist in the subsequent data collection exercise.Based on the interventions planned by York CC,the list of candidate studies was narrowed by considering factors such as its propensity to induce significant re-routing and its impact on the peak periods.Effectively the motivation here was to identify interventions that were likely to have a large impact on delays,since route choice impacts would then likely be more significant and more easily distinguished from ambient variability.This was notably at odds with the objectives of York CC,170 D.Watling et al./Transportation Research Part A46(2012)167–189in that they wished to minimise disruption,and so where possible York CC planned interventions to take place at times of day and of the year where impacts were minimised;therefore our own requirement greatly reduced the candidate set of studies to monitor.A further consideration in study selection was its timing in the year for scheduling before/after surveys so to avoid confounding effects of known significant‘seasonal’demand changes,e.g.the impact of the change between school semesters and holidays.A further consideration was York’s role as a major tourist attraction,which is also known to have a seasonal trend.However,the impact on car traffic is relatively small due to the strong promotion of public trans-port and restrictions on car travel and parking in the historic centre.We felt that we further mitigated such impacts by sub-sequently choosing to survey in the morning peak,at a time before most tourist attractions are open.Aside from the question of which intervention to survey was the issue of what data to collect.Within the resources of the project,we considered several options.We rejected stated preference survey methods as,although they provide a link to personal/socio-economic drivers,we wanted to compare actual behaviour with a network model;if the stated preference data conflicted with the network model,it would not be clear which we should question most.For revealed preference data, options considered included(i)self-completion diaries(Mahmassani and Jou,2000),(ii)automatic tracking through GPS(Jan et al.,2000;Quiroga et al.,2000;Taylor et al.,2000),and(iii)licence plate surveys(Schaefer,1988).Regarding self-comple-tion surveys,from our own interview experiments with self-completion questionnaires it was evident that travellersfind it relatively difficult to recall and describe complex choice options such as a route through an urban network,giving the po-tential for significant errors to be introduced.The automatic tracking option was believed to be the most attractive in this respect,in its potential to accurately map a given individual’s journey,but the negative side would be the potential sample size,as we would need to purchase/hire and distribute the devices;even with a large budget,it is not straightforward to identify in advance the target users,nor to guarantee their cooperation.Licence plate surveys,it was believed,offered the potential for compromise between sample size and data resolution: while we could not track routes to the same resolution as GPS,by judicious location of surveyors we had the opportunity to track vehicles across more than one location,thus providing route-like information.With time-stamped licence plates, the matched data would also provide journey time information.The negative side of this approach is the well-known poten-tial for significant recording errors if large sample rates are required.Our aim was to avoid this by recording only partial licence plates,and employing statistical methods to remove the impact of‘spurious matches’,i.e.where two different vehi-cles with the same partial licence plate occur at different locations.Moreover,extensive simulation experiments(Watling,1994)had previously shown that these latter statistical methods were effective in recovering the underlying movements and travel times,even if only a relatively small part of the licence plate were recorded,in spite of giving a large potential for spurious matching.We believed that such an approach reduced the opportunity for recorder error to such a level to suggest that a100%sample rate of vehicles passing may be feasible.This was tested in a pilot study conducted by the project team,with dictaphones used to record a100%sample of time-stamped, partial licence plates.Independent,duplicate observers were employed at the same location to compare error rates;the same study was also conducted with full licence plates.The study indicated that100%surveys with dictaphones would be feasible in moderate trafficflow,but only if partial licence plate data were used in order to control observation errors; for higherflow rates or to obtain full number plate data,video surveys should be considered.Other important practical les-sons learned from the pilot included the need for clarity in terms of vehicle types to survey(e.g.whether to include motor-cycles and taxis),and of the phonetic alphabet used by surveyors to avoid transcription ambiguities.Based on the twin considerations above of planned interventions and survey approach,several candidate studies were identified.For a candidate study,detailed design issues involved identifying:likely affected movements and alternative routes(using local knowledge of York CC,together with an existing network model of the city),in order to determine the number and location of survey sites;feasible viewpoints,based on site visits;the timing of surveys,e.g.visibility issues in the dark,winter evening peak period;the peak duration from automatic trafficflow data;and specific survey days,in view of public/school holidays.Our budget led us to survey the majority of licence plate sites manually(partial plates by audio-tape or,in lowflows,pen and paper),with video surveys limited to a small number of high-flow sites.From this combination of techniques,100%sampling rate was feasible at each site.Surveys took place in the morning peak due both to visibility considerations and to minimise conflicts with tourist/special event traffic.From automatic traffic count data it was decided to survey the period7:45–9:15as the main morning peak period.This design process led to the identification of two studies:2.1.Lendal Bridge study(Fig.1)Lendal Bridge,a critical part of York’s inner ring road,was scheduled to be closed for maintenance from September2000 for a duration of several weeks.To avoid school holidays,the‘before’surveys were scheduled for June and early September.It was decided to focus on investigating a significant southwest-to-northeast movement of traffic,the river providing a natural barrier which suggested surveying the six river crossing points(C,J,H,K,L,M in Fig.1).In total,13locations were identified for survey,in an attempt to capture traffic on both sides of the river as well as a crossing.2.2.Fishergate study(Fig.2)The partial closure(capacity reduction)of the street known as Fishergate,again part of York’s inner ring road,was scheduled for July2001to allow repairs to a collapsed sewer.Survey locations were chosen in order to intercept clockwiseFig.1.Intervention and survey locations for Lendal Bridge study.around the inner ring road,this being the direction of the partial closure.A particular aim wasFulford Road(site E in Fig.2),the main radial affected,with F and K monitoring local diversion I,J to capture wider-area diversion.studies,the plan was to survey the selected locations in the morning peak over a period of approximately covering the three periods before,during and after the intervention,with the days selected so holidays or special events.Fig.2.Intervention and survey locations for Fishergate study.In the Lendal Bridge study,while the‘before’surveys proceeded as planned,the bridge’s actualfirst day of closure on Sep-tember11th2000also marked the beginning of the UK fuel protests(BBC,2000a;Lyons and Chaterjee,2002).Trafficflows were considerably affected by the scarcity of fuel,with congestion extremely low in thefirst week of closure,to the extent that any changes could not be attributed to the bridge closure;neither had our design anticipated how to survey the impacts of the fuel shortages.We thus re-arranged our surveys to monitor more closely the planned re-opening of the bridge.Unfor-tunately these surveys were hampered by a second unanticipated event,namely the wettest autumn in the UK for270years and the highest level offlooding in York since records began(BBC,2000b).Theflooding closed much of the centre of York to road traffic,including our study area,as the roads were impassable,and therefore we abandoned the planned‘after’surveys. As a result of these events,the useable data we had(not affected by the fuel protests orflooding)consisted offive‘before’days and one‘during’day.In the Fishergate study,fortunately no extreme events occurred,allowing six‘before’and seven‘during’days to be sur-veyed,together with one additional day in the‘during’period when the works were temporarily removed.However,the works over-ran into the long summer school holidays,when it is well-known that there is a substantial seasonal effect of much lowerflows and congestion levels.We did not believe it possible to meaningfully isolate the impact of the link fully re-opening while controlling for such an effect,and so our plans for‘after re-opening’surveys were abandoned.3.Estimation of vehicle movements and travel timesThe data resulting from the surveys described in Section2is in the form of(for each day and each study)a set of time-stamped,partial licence plates,observed at a number of locations across the network.Since the data include only partial plates,they cannot simply be matched across observation points to yield reliable estimates of vehicle movements,since there is ambiguity in whether the same partial plate observed at different locations was truly caused by the same vehicle. Indeed,since the observed system is‘open’—in the sense that not all points of entry,exit,generation and attraction are mon-itored—the question is not just which of several potential matches to accept,but also whether there is any match at all.That is to say,an apparent match between data at two observation points could be caused by two separate vehicles that passed no other observation point.Thefirst stage of analysis therefore applied a series of specially-designed statistical techniques to reconstruct the vehicle movements and point-to-point travel time distributions from the observed data,allowing for all such ambiguities in the data.Although the detailed derivations of each method are not given here,since they may be found in the references provided,it is necessary to understand some of the characteristics of each method in order to interpret the results subsequently provided.Furthermore,since some of the basic techniques required modification relative to the published descriptions,then in order to explain these adaptations it is necessary to understand some of the theoretical basis.3.1.Graphical method for estimating point-to-point travel time distributionsThe preliminary technique applied to each data set was the graphical method described in Watling and Maher(1988).This method is derived for analysing partial registration plate data for unidirectional movement between a pair of observation stations(referred to as an‘origin’and a‘destination’).Thus in the data study here,it must be independently applied to given pairs of observation stations,without regard for the interdependencies between observation station pairs.On the other hand, it makes no assumption that the system is‘closed’;there may be vehicles that pass the origin that do not pass the destina-tion,and vice versa.While limited in considering only two-point surveys,the attraction of the graphical technique is that it is a non-parametric method,with no assumptions made about the arrival time distributions at the observation points(they may be non-uniform in particular),and no assumptions made about the journey time probability density.It is therefore very suitable as afirst means of investigative analysis for such data.The method begins by forming all pairs of possible matches in the data,of which some will be genuine matches(the pair of observations were due to a single vehicle)and the remainder spurious matches.Thus, for example,if there are three origin observations and two destination observations of a particular partial registration num-ber,then six possible matches may be formed,of which clearly no more than two can be genuine(and possibly only one or zero are genuine).A scatter plot may then be drawn for each possible match of the observation time at the origin versus that at the destination.The characteristic pattern of such a plot is as that shown in Fig.4a,with a dense‘line’of points(which will primarily be the genuine matches)superimposed upon a scatter of points over the whole region(which will primarily be the spurious matches).If we were to assume uniform arrival rates at the observation stations,then the spurious matches would be uniformly distributed over this plot;however,we shall avoid making such a restrictive assumption.The method begins by making a coarse estimate of the total number of genuine matches across the whole of this plot.As part of this analysis we then assume knowledge of,for any randomly selected vehicle,the probabilities:h k¼Prðvehicle is of the k th type of partial registration plateÞðk¼1;2;...;mÞwhereX m k¼1h k¼1172 D.Watling et al./Transportation Research Part A46(2012)167–189。
LOOKING BEYOND THE FIVE-FACTOR MODEL: COLLEGE SELF-EFFICACY AS A MODERATOR OF THE RELATIONSHIPBETWEEN TELLEGEN’S BIG THREE MODEL OF PERSONALITY AND HOLLAND’S MODEL OF VOCATIONAL INTEREST TYPESBy Elizabeth A BarrettThe Five-Factor Model (FFM) of personality and Tellegen’s Big Three Model of personality were compared to determine their ability to predict Holland’s RIASEC interest types. College self-efficacy was examined as a moderator of the relationship between Tellegen’s Big Three model and the RIASEC interest types. A sample of 194 college freshmen (i.e., less than 30 credits completed) was drawn from the psychology participant pool of a mid-sized Midwestern university. Instruments included the International Personality Item Pool (IPIP) to measure the FFM; the Multidimensional Personality Questionnaire Brief Form (MPQ-BF) to measure Tellegen’s Big Three model of personality; the College Self-Efficacy Inventory (CSEI) to measure college self-efficacy; and the Self Directed Search (SDS) to measure Holland’s RIASEC model of vocational interests. Findings from correlational analyses supported previous research regarding relationships among the FFM and the RIASEC interest types, and relationships among Tellegen’s Big Three and the RIASEC interest types. As hypothesized and tested via regressions for each of the six interest types, Tellegen’s Big Three model predicted all six vocational interests types (p < .001 for all), while the FFM only predicted two types at p < .05. College self-efficacy did not moderate the relationship between Tellegen’s Big Three and the RIASEC interest types. Implications and future research are discussed.ACKNOWLEDGEMENTSSeveral people have assisted me with the completion of this thesis, and I wish to thank the following people for their help and guidance:In acknowledgement of excellent guidance of this project, Dr. McFadden chairperson, whose knowledge and encouragement pushed the progress of this thesis and my development as a writer and researcher.Dr. Adams and Dr. Miron, committee members, who graciously gave their time and shared their expertise in the completion of this project, specifically, Dr. Adams who aided with the data analysis of this project and worked through multiple analysis problems with me.iiTABLE OF CONTENTSPage INTRODUCTION (1)THEORY AND LITERATURE REVIEW (4)Personality Traits and Vocational Interests Defined (4)The Five-Factor Model (FFM) of Personality (4)Holland’s Theory of Vocational Interest Types (5)Overlap between the FFM and RIASEC (7)Criticisms and Limitations of the FFM (9)Looking Beyond the FFM: Tellegen’s Big Three Model of Personality (11)Comparing Tellegen’s Big Three and the FFM (14)College Self-Efficacy: Moderating Role (16)Conclusion (20)METHOD (22)Participants (22)Procedure (23)Measures (23)Methods of Data Analysis and Missing Data (27)RESULTS (29)Descriptive Statistics (29)Relationship between the FFM and the RIASEC Interest Types:Hypothesis 1a-1e (29)Relationship between Tellegen’s Big Three and the RIASEC InterestTypes: Hypothesis 2a-2c (30)Comparing the FFM and Tellegen’s Big Three: Hypothesis 3 (31)College Self-Efficacy as Moderator: Hypothesis 4 (32)iiiTABLE OF CONTENTS (continued) DISCUSSION (34)The Relationship between the FFM and the RIASEC Interest Types (34)The Relationship between Tellegen’s Big Three and the RIASECInterest Types (35)Comparing Tellegen’s Big Three and the FFM (36)College Self-Efficacy as a Moderator (37)Limitations (38)Implications and Future Research (39)Conclusions (41)APPENDIXES (42)Appendix A: Tables (42)Table A-1. Holland’s Vocational Personality Types Described: RIASEC.. 43 Table A-2. Overlap Between the FFM and RIASEC (44)Table A-3. The Big Three of Tellegen measured by the MPQ: HigherOrder and Primary Trait Scales (45)Table A-4. Means, Standard Deviations, and Intercorrelations (47)Table A-5. Regression Analysis: Realistic Interest Type as DependentVariable (48)Table A-6. Regression Analysis: Investigative Interest Type as DependentVariable (48)Table A-7. Regression Analysis: Artistic Interest Type as DependentVariable (49)Table A-8. Regression Analysis: Social Interest Type as DependentVariable (49)Table A-9. Regression Analysis: Enterprising Interest Type as DependentVariable (50)Table A-10. Regression Analysis: Conventional Interest Type asDependent Variable (50)Table A-11. Hierarchical Multiple Moderated Regression Analysis:Realistic Interest Type as Dependent Variable (51)Table A-12. Hierarchical Multiple Moderated Regression Analysis:Investigative Interest Type as Dependent Variable (51)Table A-13. Hierarchical Multiple Moderated Regression Analysis:Artistic Interest Type as Dependent Variable (52)Table A-14. Hierarchical Multiple Moderated Regression Analysis: SocialInterest Type as Dependent Variable (52)Table A-15. Hierarchical Multiple Moderated Regression Analysis:Enterprising Interest Type as Dependent Variable (53)ivTABLE OF CONTENTS (continued)Table A-16. Hierarchical Multiple Moderated Regression Analysis:Conventional Interest Type as Dependent Variable (53)Appendix B: Figure (54)Figure B-1. Holland’s Hexagonal Model (55)Appendix C: Information Sheet and Surveys (56)REFERENCES (73)vINTRODUCTIONPersonality traits and vocational interests are two major individual difference domains that influence numerous outcomes associated with work and life success. For example, research has shown that congruence between personality traits and one’s vocation is related to greater job performance and job satisfaction (Barrick, Mount, & Judge, 2001; Hogan & Blake, 1999; Zak, Meir, & Kraemer, 1979). Additionally, specific personality traits are hypothesized to play a role in determining job success within related career domains (Sullivan & Hansen, 2004). Personality is a relatively enduring characteristic of an individual, and therefore could serve as a stable predictor of why people choose particular jobs and careers.Personality traits and vocational interests are linked by affecting behavior through motivational processes (Holland, 1973, 1985). Personality traits and vocational interests influence choices individuals make about which tasks and activities to engage in, how much effort to exert on those tasks, and how long to persist with those tasks (Holland, 1973, 1985; Mount, Barrick, Scullen, & Rounds, 2005). Research has shown that when individuals are in environments congruent with their interests, they are more likely to be happy because their beliefs, values, interests, and attitudes are supported and reinforced by people who are similar to them (Mount, Barrick, Scullen, & Rounds, 2005). Furthermore, research has demonstrated that personality and interests may shape career decision making and behavior; personality and interests guide the development ofknowledge and skills by providing the motivation to engage in particular types of activities (Sullivan & Hansen, 2004).As relatively stable dispositions, personality traits influence an individual’s behavior in a variety of life settings, including work (Dilchert, 2007). Individuals often prefer jobs requiring them to display behaviors that match their stable tendencies. Thus individuals will indicate a liking for occupations for which job duties and job environments correspond to their personality traits. Such a match between personal tendencies and job requirements can support adjustment and eventually occupational success, making the choice of a given job personally rewarding on multiple levels (Dilchert, 2007).People applying for jobs need to try to understand themselves more fully in order to determine if they will be satisfied with their career choices based on their personality traits. This process can be aided by vocational counselors who conduct vocational assessments. The purpose of vocational assessment is to enhance client self-understanding, promote self-exploration, and assist in realistic decision making (Carless, 1999). According to a model proposed by Carless (1999), career assessment is based on the assumption that comprehensive information about the self (e.g., knowledge of one’s personality) in relation to the world of work is a necessary prerequisite for wise career decision making.Self-efficacy beliefs--personal expectations about the ability to succeed at tasks (Bandura, 1986)--are often assessed by vocational counselors. This study examines college self-efficacy--belief in one’s ability to perform tasks necessary for success incollege (Wang & Castaneda-Sound, 2008). Self-efficacy determines the degree to which individuals initiate and persist with tasks (Bandura, 1986), and research has found that personality may influence exploration of vocational interests, through high levels of self-efficacy (Nauta, 2007).There is an abundance of literature supporting that the Five-Factor Model (FFM) (discussed in depth in following sections) of personality predicts Holland’s theory of vocational interest types; however, there is little literature that extends beyond use of the Five-Factor Model. This is due to the adoption of the FFM as an overriding model of personality over the past fifteen years. However, as will be demonstrated later, several criticisms of the model have surfaced. In light of these criticisms the purpose of this study is to extend the existing literature that has established links between the FFM and Holland’s vocational interest types, while examining the relationship between an alternate personality model, Tellegen’s Big Three (as measured by the Multidimensional Personality Questionnaire (MPQ)) and Holland’s types. Furthermore, this study will examine the moderating role that college self-efficacy plays on the relationship between Tellegen’s Big Three and Holland’s interest types.THEORY AND LITERATURE REVIEWPersonality Traits and Vocational Interests DefinedPersonality traits refer to characteristics that are stable over time and are psychological in nature; they reflect who we are and in aggregate determine our affective, behavioral, and cognitive styles (Mount, Barrick, Scullen, & Rounds, 2005). Vocational interests reflect long-term dispositional traits that influence vocational behavior primarily through one’s preferences for certain environments, activities, and types of people (Mount, Barrick, Scullen, & Rounds, 2005).The Five-Factor Model (FFM) of PersonalityThe FFM, often referred to as the Big Five personality dimensions, is a major model that claims personality consists of five dimensions: Openness to Experience (i.e., imaginative, intellectual, and artistically sensitive), Conscientiousness (i.e., dependable, organized, and persistent), Extraversion (i.e., sociable, active, and energetic), Agreeableness (i.e., cooperative, considerate, and trusting), and Neuroticism, sometimes referred to positively as emotional stability (i.e., calm, secure, and unemotional) (Harris, Vernon, Johnson, & Jang, 2006; McCrae & Costa, 1986; McCrae & Costa, 1987; Mount, Barrick, Scullen, & Rounds, 2005; Nauta, 2004; Sullivan & Hansen, 2004). The FFM provides the foundation for several personality measures (e.g., NEO-PI, NEO-PI-R, NEO-FFI) that have proved to be valid and reliable and are widely utilized in research today (Costa & McCrae, 1992). There appears to be a large degree of consensusregarding the FFM of personality and the instruments used to measure the model. For instance, the FFM has been shown to have a large degree of universality (McCrae, 2001), specifically in terms of stability across adulthood (McCrae & Costa, 2003) and cultures (DeFruyt & Mervielde, 1997; Hofstede & McCrae, 2004, McCrae, 2001).Holland’s Theory of Vocational Interest TypesHolland’s theory of vocational interests has played a key role in efforts to understand vocational interests, choice, and satisfaction.Holland was very clear that he believed personality and vocational interests are related:If vocational interests are construed as an expression of personality, then theyrepresent the expression of personality in work, school subjects, hobbies,recreational activities, and preferences. In short, what we have called ‘vocational interests’ are simply another aspect of personality…If vocational interests are anexpression of personality, then it follows that interest inventories are personalityinventories. (Holland, 1973, p.7)Vocational interest types, as classified by Holland, are six broad categories (discussed later in the section) that can be used to group occupations or the people who work in them. Holland’s theory of vocational interest types and work environments states that employees’ satisfaction with a job as well as propensity to leave that job depends on the degree to which their personalities match their occupational environments (Holland, 1973, 1985). Furthermore, people are assumed to be most satisfied, successful, and stable in a work environment that is congruent with their vocational interest type. Two ofHolland’s basic assumptions are: (a) individuals in a particular vocation have similar personalities, and (b) individuals tend to choose occupational environments consistent with their personality (Holland, 1997).A fundamental proposition of Holland’s theory is that, when differentiated by their vocational interests, people can be categorized according to a taxonomy of six types, hereinafter collectively referred to as RIASEC (Holland, 1973, 1985). Holland’s theory states that six vocational interest types--Realistic, Investigative, Artistic, Social, Enterprising, and Conventional (RIASEC)--influence people to seek environments which are congruent with their characteristics (Harris, Vernon, Johnson, & Jang, 2006; Holland, 1973, 1985; Nauta, 2004; Roberti, Fox, & Tunick, 2003; Sullivan & Hansen, 2004; Zak, Meir, & Kraemer, 1979). Holland used adjective descriptors to capture the distinctive characteristics of each interest type (Hogan & Blake, 1999). These are summarized in Table A-1. Holland’s approach to the assessment of vocational interest types was based on the assumption that members of an occupational group have similar work-related preferences and respond to problems and situations in similar ways (Carless, 1999).Realistic types like the systematic manipulation of machinery, tools, or animals. Investigative types have interests that involve analytical, curious, methodical, and precise activities. The interests of Artistic types are expressive, nonconforming, original, and introspective. Social types want to work with and help others. Enterprising types seek to influence others to attain organizational goals or economic gain. Finally, Conventional types are interested in systematic manipulation of data, filing records, or reproducing materials (Tokar, Vaux, & Swanson, 1995).According to Holland’s theory, these interest types differ in their relative similarity to one another, in ways that can be represented by a hexagonal figure with the types positioned at the six points (see Figure B-1). Adjacent types (e.g., Realistic and Investigative) are most similar; opposite types (e.g., Realistic and Social) are least similar, and alternating types (e.g., Realistic and Artistic) are assumed to have an intermediate level of relationship (Holland, 1973, 1985; Tokar, Vaux, & Swanson, 1995).Overlap between the FFM and RIASECMany studies provide evidence of the links between the FFM of personality and the RIASEC interest types. An extensive review of the research investigating the links between the FFM and the RIASEC types identified ten studies that found Extraversion predicts interest in jobs that focus on Social and Enterprising interests. Ten studies showed Openness to Experience predicts interest in jobs that focus on Investigative and Artistic interests. Six studies found Agreeableness predicts interest in jobs that focus on Social interest; six studies showed Conscientiousness predicts interests in jobs that focus on Conventional interests; and one study found Neuroticism predicts interests in jobs that focus on Investigative interests (see Table A-2 for the citations). One discrepancy in this research has been Costa and McCrae’s claims that the FFM applies uniformly to all adult ages, but Mroczek, Ozer, Spiro, and Kaiser (1998) found substantial differences between the structures emerging from older individuals as compared to undergraduate students, in that the five factor structure failed to emerge in the student sample (i.e., agreeableness failed to emerge) as it did with the older sample.All of the links discussed between the FFM of personality and the RIASEC interest types provide the foundation for hypotheses 1a – 1e. Hypotheses 1a – 1e will add to the literature, previously discussed, by assessing current college students early in their college careers. These are the people who have the potential to be most influenced by vocational and career counselors. Given that research has found a discrepancy in FFM profiles of younger and older individuals, it is important to test its efficacy in predicting vocational interests.Hypothesis 1a (H1a): Extraversion will significantly positively correlate withSocial and Enterprising types, but not Realistic, Investigative, Artistic, andConventional types.Hypothesis 1b (H1b): Openness to Experience will significantly positivelycorrelate with Investigative and Artistic types, but not Realistic, Conventional,Social, and Enterprising types.Hypothesis 1c (H1c): Agreeableness will significantly positively correlate withSocial types, but not Realistic, Conventional, Enterprising, Investigative, andArtistic types.Hypothesis 1d (H1d): Conscientiousness will significantly positively correlatewith Conventional types, but not Realistic, Enterprising, Investigative, Social, and Artistic types.Hypothesis 1e (H1e): Neuroticism will significantly negatively correlate withInvestigative types, but not Realistic, Enterprising, Conventional, Social, andArtistic types.Criticisms and Limitations of the FFMThe whole enterprise of science depends on challenging accepted views, and the FFM has become one of the most accepted models in personality research. Many critiques of the FFM ask “Why are there five and only five factors? Five factor protagonists say: it is an empirical fact…via the mathematical method of factor analysis, the basic dimensions of personality have been discovered.” (McCrae & Costa, 1989, p. 120). Has psychology as a science achieved a final and absolute way of looking at personality or is there a way to further our conceptualization of personality? In the article by Costa and McCrae (1997) explaining the anticipated changes to the NEO in the new millennium, they anticipate only minor wording modifications and simplifications. Thus it appears as if the FFM is viewed as a final or almost final achievement (Block, 2001). One claimed benefit of the FFM is evidence of heritability is strong for all 5 factors, but evidence is strong for all personality factors studied; it does not single out the Costa and McCrae factors (Eysenck, 1992). In other words, all the criteria suggested by Costa and McCrae are necessary but not sufficient to mark out one model from many which also conform to this criteria.The debate that has been most prominent over the past 15 years, and which has probably attracted the most attention, concerns the number and description of the basic, fundamental, highest-order factors of personality. Evidence from meta-analyses of factorial studies provide evidence that three, not five personality factors, emerge at the highest level of analysis (Royce & Powell, 1983; Tellegen & Waller, 1991; Zuckerman, Kuhlman, & Camac, 1988; Zuckerman, Kuhlman, Thornquist, & Kiers, 1991).Altogether, Eysenck (1992) has surveyed many different models, questionnaires and inventories, reporting in most cases a break-down into 2 or 3 major factors; but never 5. Additionally, Jackson, Furnham, Forde, and Cotter (2000) and Tellegen (1985) have contradicted Costa and McCrae’s (1995) assertions that a five-factor model seems most appropriate, with results showing that a three-factor solution is both more clear and parsimonious.Another critique of the FFM lies in its development. The initial factor-analytic derivations of the Big Five were not guided by explicit psychological theory, and therefore some have asked the question, “Why these five?” (e.g., Revelle, 1987; Waller & Ben-Porath, 1987). As Briggs (1989) points out, the original studies leading to the FFM “prompted no a priori predictions as to what factors should emerge, and a coherent and falsifiable explanation for the five factors has yet to be put forward” (p. 249).A further developmental critique of the FFM is the lack of lower order factors. Theoretically, factors exist at different hierarchical levels, and the FFM only measures five higher order factors (Block, 2001). The FFM operates at a broadband level to measure the main (i.e., higher order) categories of traits (McAdams, 1992). Within each of the five categories, therefore, may be many different and more specific traits, as traits are nested hierarchically within traits (McAdams, 1992).Another limitation of the FFM lies in researchers’ inability to consistently link the personality traits to the Holland interest types. Research has found that although there is a significant overlap between the FFM and RIASEC interest types, the RIASEC types do not appear to be entirely encompassed by the Big-Five personality dimensions (Carless,1999; Church, 1994; DeFruyt & Mervielde, 1999; Tokar, Vaux, & Swanson, 1995). Three personality dimensions in the FFM predict the RIASEC types, but there is less evidence to support that the other two predict the RIASEC types. Specifically, there appears to be significant overlap with Conscientiousness, Openness, and Extraversion in predicting the RIASEC interest types, but less research has been able to find links between Agreeableness and Neuroticism with the RIASEC interest types. This is a limitation of the FFM in relating to vocational interests (Costa, McCrae, & Holland, 1984; Gottfredson, Jones, & Holland, 1993; Tokar, Vaux, & Swanson, 1995).Looking Beyond the FFM: Tellegen’s Big Three Model of PersonalityIn light of these criticisms of the FFM, it seems attention could be paid to alternate models of personality to investigate the dimensions underlying Holland’s interest types. The literature base is sparse here, and alternative personality models warrant further study, particularly with regard to vocational interests (Blake & Sackett, 1999; Church, 1994; Larson & Borgen, 2002; Staggs, Larson, & Borgen, 2003). One such model is Tellegen’s Big Three which addresses many of the criticisms of the FFM.Many vocational psychology researchers use the Big Five model of personality, often measured by the NEO-PI or NEO-PI-R, but less often the Big Three model of personality measured by the Multidimensional Personality Questionnaire (MPQ) is used (Tellegen, 1985; Tellegen & Waller, 1991). This model of personality resulted from ten years of research on focal dimensions in the personality literature (Tellegen, 1985; Tellegen & Waller, 1991). Tellegen’s (1985; Tellegen & Waller, 1991) Big Three modeldefines three higher order factors. These represent the clusters of items from a factor analysis that composed the three higher order traits. The lower order factors consist of items clustered in each of the higher order factors. The higher order factors are: Positive Emotionality (PEM), Negative Emotionality (NEM), and Constraint (CT) (Tellegen, 1985; Tellegen & Waller, 1991). These higher order traits correlate minimally with one another and encompass 11 lower order traits. Refer to Table A-3 for a description of the three higher order traits and the 11 lower order traits.There are only three published studies that have examined the Big Three model as relating to vocational interests. Blake and Sackett (1999) reported that the Artistic type moderately related with the MPQ Absorption lower order trait (Larson & Borgen, 2002). The Social type negatively related to the MPQ Aggression lower order trait; the Enterprising type related moderately to the MPQ Social Potency lower order trait; and the Conventional type related moderately to the MPQ Control lower order trait.Staggs, Larson, and Borgen (2003) also analyzed the lower order traits, specifically, as opposed to the higher order factors of PEM, NEM, and CT. They identified seven personality dimensions that have a substantial relationship with vocational interests: Absorption predicted interest in Artistic occupations; Social Potency predicted interest in Enterprising occupations; Harm Avoidance predicted interest in science and mechanical activity occupations; Achievement predicted interest in science and mathematic occupations; Social Closeness predicted interest in mechanical activity occupations; Traditionalism predicted interest in religious activities; and Stress Reaction predicted interest in athletic careers. Staggs, Larson, and Borgen (2003) used a collegestudent sample, but were not studying the RIASEC types; they were using a different conceptualization of vocational interests as measured by the Strong Interest Inventory which measures General Occupational Themes.Larson and Borgen (2002) found that the PEM factor was more strongly correlated with Social interests than with Enterprising interests; however, PEM did strongly correlate with all six RIASEC types (p < .001). This finding shows strong evidence that the PEM higher order trait relates to the RIASEC types. Larson and Borgen (2002) also found that the CT factor was negatively related to Realistic and Artistic interest types, and that the NEM factor was negatively related to Artistic interest types. Larson and Borgen (2002) utilized a sample of “gifted” adolescent students, which is a very limited and non-generalizable sample. In contrast, the current study tests a freshman college student sample, which is more generalizable to the population of students who are seeking vocational guidance.The links between the MPQ and the RIASEC interest types are under-researched. Although some vocational research has utilized the MPQ, more needs to be done to determine the relationships between Tellegen’s Big Three and Holland’s RIASEC interest types. However, the research provides support for the idea that there are alternative personality dimensions (i.e., Tellegen’s Big Three), outside of the FFM, that can significantly predict vocational interests, in particular the RIASEC types. Hypotheses 2a – 2c will test relationships between the Tellegen’s Big Three (as measured by the MPQ-BF) and the RIASEC interest types.Hypothesis 2a (H2a): The PEM factor will significantly positively correlate with all six RIASEC types.Hypothesis 2b (H2b): The CT factor will significantly negatively correlate withRealistic and Artistic types, but not with Investigative, Social, Enterprising, andConventional types.Hypothesis 2c (H2c): The NEM factor will significantly negatively correlate with Artistic types, but not with Investigative, Social, Enterprising, Realistic, andConventional types.Comparing Tellegen’s Big Three and the FFMAn earlier discussion proposed criticisms of the FFM. In light of these criticisms an alternate personality model was considered: Tellegens’ Big Three, measured by the MPQ. This model of personality resolves all the previous criticisms of the FFM: five versus 3 factors, lack of lower order factors, and model development issues.Tellegen’s (1985) understanding of personality differs from the conception of the FFM. Tellegen believes personality can be summed by three overriding traits or factors versus the 5 factors of the FFM. This is an inherent difference in the two models of personality, which guided the development of instruments used to measure these models, in terms of a three versus a five factor structure. Furthermore, Tellegen (1985) utilized a bottom-up approach to development of the MPQ, in which constructs were based on iterative cycles of data collection and item analyses designed to better differentiate the primary scales. In contrast, Tupes and Chrtistal (1961) emphasized deductive, top-down。
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population 母体sample 样本census 普查sampling 抽样quantitative 量的qualitative/categorical质的discrete 离散的continuous 连续的population parameters 母体参数sample statistics 样本统计量descriptive statistics 叙述统计学inferential/inductive statistics 推论 ...抽样调查（sampliing survey单纯随机抽样（simple random sampling 系统抽样（systematic sampling分层抽样（stratified sampling整群抽样（cluster sampling多级抽样（multistage sampling常态分配(Parametric Statistics)无母数统计学(Nonparametric Statistics)实验设计(Design of Experiment)参数(Parameter)Data analysis 资料分析Statistical table 统计表Statistical chart 统计图Pie chart 圆饼图Stem-and-leaf display 茎叶图Box plot 盒须图Histogram 直方图Bar Chart 长条图Polygon 次数多边图Ogive 肩形图Descriptive statistics 叙述统计学Expectation 期望值Mode 众数Mean 平均数Variance 变异数Standard deviation 标准差Standard error 标准误Covariance matrix 共变异数矩阵Inferential statistics 推论统计学Point estimation 点估计Interval estimation 区间估计Confidence interval 信赖区间Confidence coefficient 信赖系数Testing statistical hypothesis 统计假设检定Regression analysis 回归分析Analysis of variance 变异数分析Correlation coefficient 相关系数Sampling survey 抽样调查Census 普查Sampling 抽样Reliability 信度Validity 效度Sampling error 抽样误差Non-sampling error 非抽样误差Random sampling 随机抽样Simple random sampling 简单随机抽样法Stratified sampling 分层抽样法Cluster sampling 群集抽样法Systematic sampling 系统抽样法Two-stage random sampling 两段随机抽样法Convenience sampling 便利抽样Quota sampling 配额抽样Snowball sampling 雪球抽样Nonparametric statistics 无母数统计The sign test 等级检定Wilcoxon signed rank tests 魏克森讯号等级检定Wilcoxon rank sum tests 魏克森等级和检定Run test 连检定法Discrete uniform densities 离散的均匀密度Binomial densities 二项密度Hypergeometric densities 超几何密度Poisson densities 卜松密度Geometric densities 几何密度Negative binomial densities 负二项密度Continuous uniform densities 连续均匀密度Normal densities 常态密度Exponential densities 指数密度Gamma densities 伽玛密度Beta densities 贝他密度Multivariate analysis 多变量分析Principal components 主因子分析Discrimination analysis 区别分析Cluster analysis 群集分析Factor analysis 因素分析Survival analysis 存活分析Time series analysis 时间序列分析Linear models 线性模式Quality engineering 品质工程Probability theory 机率论Statistical computing 统计计算Statistical inference 统计推论Stochastic processes 随机过程Decision theory 决策理论Discrete analysis 离散分析Mathematical statistics 数理统计统计学: Statistics母体: Population样本: Sample资料分析: Data analysis统计表: Statistical table统计图: Statistical chart圆饼图: Pie chart茎叶图: Stem-and-leaf display盒须图: Box plot直方图: Histogram长条图: Bar Chart次数多边图: Polygon肩形图: Ogive叙述统计学: Descriptive statistics期望值: Expectation众数: Mode平均数: Mean变异数: Variance标准差: Standard deviation标准误: Standard error共变异数矩阵: Covariance matrix推论统计学: Inferential statistics点估计: Point estimation区间估计: Interval estimation信赖区间: Confidence interval信赖系数: Confidence coefficient统计假设检定: Testing statistical hypothesis回归分析: Regression analysis变异数分析: Analysis of variance相关系数: Correlation coefficient抽样调查: Sampling survey普查: Census抽样: Sampling信度: Reliability效度: Validity抽样误差: Sampling error非抽样误差: Non-sampling error随机抽样: Random sampling简单随机抽样法: Simple random sampling 分层抽样法: Stratified sampling群集抽样法: Cluster sampling系统抽样法: Systematic sampling两段随机抽样法: Two-stage randomsampling便利抽样: Convenience sampling配额抽样: Quota sampling雪球抽样: Snowball sampling无母数统计: Nonparametric statistics等级检定: The sign test魏克森讯号等级检定: Wilcoxon signed ranktests魏克森等级和检定: Wilcoxon rank sum tests连检定法: Run test离散的均匀密度: Discrete uniform densities二项密度: Binomial densities超几何密度: Hypergeometric densities卜松密度: Poisson densities几何密度: Geometric densities负二项密度: Negative binomial densities连续均匀密度: Continuous uniform densities常态密度: Normal densities指数密度: Exponential densities伽玛密度: Gamma densities贝他密度: Beta densities多变量分析: Multivariate analysis主因子分析: Principal components区别分析: Discrimination analysis群集分析: Cluster analysis因素分析: Factor analysis存活分析: Survival analysis时间序列分析: Time series analysis 线性模式: Linear models品质工程: Quality engineering机率论: Probability theory统计计算: Statistical computing统计推论: Statistical inference随机过程: Stochastic processes决策理论: Decision theory离散分析: Discrete analysis数理统计: Mathematical statistics 统计名词市调辞典众数(Mode) 普查(census)指数(Index) 问卷(Questionnaire)中位数(Median) 信度(Reliability)百分比(Percentage) 母群体(Population)信赖水准(Confidence level) 观察法(Observational Survey)假设检定(Hypothesis Testing) 综合法(Integrated Survey)卡方检定(Chi-square Test) 雪球抽样(Snowball Sampling)差距量表(Interval Scale) 序列偏差(SeriesBias)类别量表(Nominal Scale) 次级资料(Secondary Data)顺序量表(Ordinal Scale) 抽样架构(Samplingframe)比率量表(Ratio Scale) 集群抽样(ClusterSampling)连检定法(Run Test) 便利抽样(ConvenienceSampling)符号检定(Sign Test) 抽样调查(Sampling Sur)算术平均数(Arithmetic Mean) 非抽样误差(non-sampling error)展示会法(Display Survey)调查名词准确效度(Criterion-RelatedValidity)元素(Element) 邮寄问卷法(Mail Interview)样本(Sample) 信抽样误差(Sampling error)效度(Validity) 封闭式问题(Close Question)精确度(Precision) 电话访问法(TelephoneInterview)准确度(Validity) 随机抽样法(Random Sampling)实验法(Experiment Survey)抽样单位(Sampling unit) 资讯名词市场调查(Marketing Research) 决策树(Decision Trees)容忍误差(Tolerated erro) 资料采矿(Data Mining)初级资料(Primary Data) 时间序列(Time-Series Forecasting)目标母体(Target Population) 回归分析(Regression)抽样偏差(Sampling Bias) 趋势分析(Trend Analysis)抽样误差(sampling error) 罗吉斯回归(Logistic Regression)架构效度(Construct Validity) 类神经网络(Neural Network)配额抽样(Quota Sampling) 无母数统计检定方法(Non-Parametric Test)人员访问法(Interview) 判别分析法(Discriminant Analysis)集群分析法(cluster analysis) 规则归纳法(Rules Induction)内容效度(Content Validity) 判断抽样(Judgment Sampling)开放式问题(Open Question) OLAP(OnlineAnalytical Process)分层随机抽样(Stratified Random sampling)资料仓储(Data Warehouse)非随机抽样法(Nonrandom Sampling) 知识发现(Knowledge DiscoveryAbsolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additive Noise, 加性噪声Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alpha factoring,α因子法Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis Of Effects, 效应分析Analysis Of Variance, 方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA （analysis of variance）, 方差分析ANOVA Models, 方差分析模型ANOVA table and eta, 分组计算方差分析Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area 区域图Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Collinearity, 共线性Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照, 质量控制图Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation, 相关性Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Crosstabs 列联表分析Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve Estimation, 曲线拟合Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Direct Oblimin, 斜交旋转Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法Error Bar, 均值相关区间图Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explained variance （已说明方差）Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查Generalized least squares, 综合最小平方法GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点High-Low, 低区域图Higher Order Interaction Effects，高阶交互作用HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Image factoring,, 多元回归法Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K-Means Cluster逐步聚类分析K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least Squared Criterion，最小二乘方准则Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Leveage Correction，杠杆率校正Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形MSC（多元散射校正）Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal P-P, 正态概率分布图Normal Q-Q, 正态概率单位分布图Normal ranges, 正常范围Normal value, 正常值Normalization 归一化Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Pareto, 直条构成线图（又称佩尔托图）Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式PCA（主成分分析）Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 构成图,饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡PLS（偏最小二乘法）Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal axis factoring,主轴因子法Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling,按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和residual variance (剩余方差)Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequence, 普通序列图Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significant Level, 显著水平Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science),SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层（复数）Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法。
spss常用统计词汇中英对照表统计词汇英汉对照Absolute deviation, 绝对离差Absolute number, 绝对数 Absolute residuals, 绝对残差Acceptable hypothesis, 可接受假设 Accumulation, 累积ccuracy, 准确度 Actual frequency, 实际频数Addition, 相加 Additivity, 可加性Adjusted rate, 调整率 Adjusted value, 校正值Admissible error, 容许误差 Aggregation, 聚集性Alternative hypothesis, 备择假设 Among groups, 组间Amounts, 总量 Analysis of correlation, 相关分析Analysis of covariance, 协方差分析 Analysis of regression, 回归分析Analysis of time series, 时间序列分析 Analysis of variance, 方差分析ANOVA （analysis of variance）, 方差分析 ANOVA Models, 方差分析模型Arcing, 弧/弧旋 Arcsine transformation, 反正弦变换Area under the curve, 曲线面积 AREG , 评估从一个时间点到下一个时间点回归相关时的误差Arithmetic mean, 算术平均数rrhenius relation, 艾恩尼斯关系 Assessing fit, 拟合的评估Asymmetric distribution, 非对称分布 Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差 Attributable risk, 归因危险度Attribute data, 属性资料 Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数 Average confidence interval length, 平均置信区间长度 Average growth rate, 平均增长率Bar chart, 条形图 Bar graph, 条形图Base period, 基期 Bayes" theorem , Bayes 定理Bell-shaped curve, 钟形曲线 Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量 Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归 Binomial distribution, 二项分布Bisquare, 双平方 Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体 Biweight M-estimator, 双权 M 估计量 BMDP(Biomedical puter programs), BMDP 统计软件包 Bo_plots, 箱线图/箱尾图Canonical correlation, 典型相关 Caption, 纵标目Case-control study, 病例对照研究 Categorical variable, 分类变量Catenary, 悬链线 Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系 Cell, 单元Censoring, 终检 Center of symmetry, 对称中心Centering and scaling, 中心化和定标 Central tendency, 集中趋势Central value, 中心值 CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差 Chance variable, 随机变量Characteristic equation, 特征方程 Characteristic root, 特征根Characteristic vector, 特征向量 Chebshev criterion of fit, 拟合的切比雪夫准则 Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2 检验 Choleskey deposition, 乔洛斯基分解 Circle chart, 圆图Class interval, 组距Class mid-value, 组中值 Class upper limit, 组上限Classified variable, 分类变量 Cluster analysis, 聚类分析Cluster sling, 整群抽样 Coefficient of contingency,列联系数Coefficient of determination, 决定系数 Coefficient of multiple correlation, 多重相关系数 Coefficient of partial correlation, 偏相关系数 Coefficient of production-moment correlation, 积差相关系数 Coefficient of rank correlation, 等级相关系数 Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数 Coefficient of variation, 变异系数Cohort study, 队列研究 Column, 列Column effect, 列效应 Column factor, 列因素bination pool, 合并 binative table, 组合表mon factor, 共性因子 mon regression coefficient, 公共回归系数 mon value, 共同值mon variance, 公共方差mon variation, 公共变异munality variance, 共性方差 parability, 可比性parison of bathes, 批比较 parison value, 比较值partment model, 分部模型 passion, 伸缩plement of an event, 补事件 plete association, 完全正相关plete dissociation, 完全不相关 plete statistics, 完备统计量pletely randomized design, 完全随机化设计 posite event, 联合事件posite events, 复合事件 Concavity, 凹性Conditional e_pectation, 条件期望 Conditional likelihood, 条件似然Conditional probability, 条件概率 Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限 Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confounding factor, 混杂因素Conjoint, 联合分析 Consistency, 相合性Consistency check, 一致性检验 Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Contour, 边界线Contribution rate, 贡献率 Control, 对照Controlled e_periments, 对照实验 Conventional depth, 常规深度Corrected factor, 校正因子 Corrected mean, 校正均值Correction coefficient, 校正系数 Correctness, 正确性Correlation coefficient, 相关系数Correlation inde_, 相关指数Counting, 计数 Counts, 计数/频数Covariance, 协方差 Co_ Regression, Co_ 回归Criteria for fitting, 拟合准则 Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域 Critical value, 临界值Cumulative distribution function, 分布函数 D test, D 检验Data acquisition, 资料收集 Data bank, 数据库Data capacity, 数据容量 Data deficiencies, 数据缺乏Data handling, 数据处理 Data manipulation, 数据处理Data processing, 数据处理 Data set, 数据集Data sources, 数据来源 Data transformation, 数据变换Data validity, 数据有效性 Data-in, 数据输入Data-out, 数据输出 Degree of freedom, 自由度Degree of reliability, 可靠性程度 Density function, 密度函数Density of data points, 数据点的密度 Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度 Derivative matri_, 导数矩阵Derivative-free methods, 无导数方法 Design, 设计Determinacy, 确定性 Determinant, 行列式Determinant, 决定因素 Deviation, 离差Deviation from average, 离均差Dichotomous variable, 二分变量Differential equation, 微分方程 Direct standardization, 直接标准化法 Discrete variable, 离散型变量 DISCRIMINANT, 判断Discriminant analysis, 判别分析 Discriminant coefficient, 判别系数Discriminant function, 判别值 Dispersion, 散布/分散度Downward rank, 降秩 Effect, 实验效应Eigenvalue, 特征值 Eigenvector, 特征向量Ellipse, 椭圆 Empirical distribution, 经验分布Empirical probability, 经验概率单位 Enumeration data, 计数资料Equally likely, 等可能 Equivariance, 同变性Error, 误差/错误 Error of estimate, 估计误差Error type I, 第一类错误 Error type II, 第二类错误Estimated error mean squares, 估计误差均方 Estimated error sum of squares, 估计误差平方和 Euclidean distance, 欧式距离Event, 事件 Event, 事件E_ceptional data point, 异常数据点 E_pected values, 期望值E_periment, 实验 E_perimental sling, 试验抽样E_perimental unit, 试验单位 E_planatory variable, 说明变量E_ploratory data analysis, 探索性数据分析 E_plore Summarize, 探索-摘要E_ponential curve, 指数曲线 E_ponential growth, 指数式增长E_SMOOTH, 指数平滑方法E_tended fit, 扩充拟合E_tra parameter, 附加参数E_trapolation, 外推法E_treme observation, 末端观测值 E_tremes, 极端值/极值F distribution, F 分布 F test, F 检验Factor, 因素/因子 Factor analysis, 因子分析Factor Analysis, 因子分析 Factor score, 因子得分Family of distributions, 分布族 Field investigation, 现场调查Field survey, 现场调查 Finite population, 有限总体Finite-sle, 有限样本 First derivative, 一阶导数First principal ponent, 第一主成分 First quartile, 第一四分位数Fitted value, 拟合值 Fitting a curve, 曲线拟合Fi_ed base, 定基 Fluctuation, 随机起伏Forecast, 预测 Four fold table, 四格表Fourth, 四分点 Fraction blow, 左侧比率Fractional error, 相对误差 Frequency, 频率Frequency polygon, 频数多边图 Frontier point, 界限点Function relationship, 泛函关系 Gamma distribution, 伽玛分布Gauss increment, 高斯增量 Gaussian distribution, 高斯分布/正态分布General census, 全面普查 GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Grand mean, 总均值Group averages, 分组平均 Grouped data, 分组资料Guessed mean, 假定平均数 Half-life, 半衰期Happenstance, 偶然事件 Harmonic mean, 调和均数Hazard function, 风险均数 Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法HILOGLINEAR, 多维列联表的层次对数线性模型 Hinge, 折叶点Histogram, 直方图 HOMALS, 多重响应分析Homogeneity of variance, 方差齐性 Homogeneity test, 齐性检验Huber M-estimators, 休伯 M 估计量 Hyperbola, 双曲线Hypothesis testing, 假设检验 Hypothetical universe, 假设总体Impossible event, 不可能事件 Independence, 独立性Independent variable, 自变量 Inde_, 指标/指数Indirect standardization, 间接标准化法 Individual, 个体Inference band, 推断带 Infinite population, 无限总体Infinitely great, 无穷大 Infinitely small, 无穷小Influence curve, 影响曲线 Information capacity, 信息容量Initial condition, 初始条件 Initial estimate, 初始估计值Initial level, 最初水平 Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法 Interquartile range, 四分位距Interval estimation, 区间估计 Intervals of equal probability, 等概率区间 Intrinsic curvature, 固有曲率Invariance, 不变性 Inverse matri_, 逆矩阵Inverse probability, 逆概率 Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式 Joint distribution function, 分布函数 Joint probability, 联合概率 Jointprobability distribution, 联合概率分布 K means method, 逐步聚类法Kaplan-Merier chart, Kaplan-Merier 图 Kendall"s rank correlation, Kendall 等级相关 Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 Kruskal and Wallis test, Kruskal 及 Wallis 检验/多样本的秩和检验/H 检验 Kurtosis, 峰度Lack of fit, 失拟 Ladder of powers, 幂阶梯Large sle, 大样本 Large sle test, 大样本检验Latin square, 拉丁方 Latin square design, 拉丁方设计Least favorable configuration, 最不利构形 Least favorable distribution, 最不利分布 Least significant difference, 最小显著差法 Least square method, 最小二乘法Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合 Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L 估计量 L-estimator of location, 位置 L 估计量L-estimator of scale, 尺度 L 估计量 Level, 水平Life table, 寿命表 Life table method, 生命表法Light-tailed distribution, 轻尾分布 Likelihood function, 似然函数Likelihood ratio, 似然比 line graph, 线图Linear correlation, 直线相关 Linear equation, 线性方程Linear programming, 线性规划 Linear regression, 直线回归Linear Regression, 线性回归 Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性 Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换 Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布 Logit transformation, Logit 转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数 Low correlation, 低度相关Lower limit, 下限 Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应 Marginal density function, 边缘密度函数 Marginal probability, 边缘概率 Marginal probability distribution, 边缘概率分布 Matching of transformation, 变换的匹配Mathematical e_pectation, 数学期望Mathematical model, 数学模型Ma_imum L-estimator, 极大极小 L 估计量 Ma_imum likelihood method, 最大似然法 Mean, 均数 Mean squares between groups, 组间均方 Mean squares within group, 组内均方 Means (pare means), 均值-均值比较 Median, 中位数Median effective dose, 半数效量Median polish, 中位数平滑 Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量 Minimum distance estimation, 最小距离估计 Minimum variance estimator, 最小方差估计量 MINITAB, 统计软件包Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计 Models for outliers, 离群值模型Modifying the model, 模型的修正 Most favorable configuration, 最有利构形Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple parison, 多重比较Multiple correlation , 复相关 Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归 Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应 Multi-stage sling, 多阶段抽样Multivariate T distribution, 多元 T 分布 Mutuale_clusive, 互不相容Mutual independence, 互相独立 Negative correlation, 负相关Negative linear correlation, 负线性相关 Negatively skewed, 负偏Newman-Keuls method, q 检验 NK method, q 检验No statistical significance, 无统计意义 Nominal variable, 名义变量Nonlinear regression, 非线性相关 Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验 Normal deviate, 正态离差Normal distribution, 正态分布 Normal ranges, 正常范围Normal value, 正常值 Nuisance parameter, 多余参数/讨厌参数 Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数 Observation unit, 观察单位Observed value, 观察值 One sided test, 单侧检验One-way analysis of variance, 单因素方差分析 Oneway ANOVA , 单因素方差分析Order statistics, 顺序统计量 Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基 Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件 ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Paired design, 配对设计Paired sle, 配对样本 Parallel tests, 平行试验Parameter, 参数 Parametric statistics, 参数统计Parametric test, 参数检验 Partial correlation, 偏相关Partial regression, 偏回归 Pearson curves, 皮尔逊曲线Percent bar graph, 百分条形图 Percentage, 百分比Percentile, 百分位数 Percentile curves, 百分位曲线Periodicity, 周期性 Permutation, 排列P-estimator, P 估计量 Pie graph, 饼图Pitman estimator, 皮特曼估计量 Point estimation, 点估计Poisson distribution, 泊松分布 Population, 总体Positive correlation, 正相关 Positively skewed, 正偏Posterior distribution, 后验分布 Power of a test, 检验效能Precision, 精密度 Predicted value, 预测值Principal ponent analysis, 主成分分析 Prior distribution, 先验分布Prior probability, 先验概率 Probabilistic model, 概率模型probability, 概率 Probability density, 概率密度Product moment, 乘积矩/协方差 Pro, 截面迹图Proportion, 比/构成比 Proportion allocation in stratified random sling, 按比例分层随机抽样 Proportionate sub-class numbers, 成比例次级组含量Pseudo F test, 近似 F 检验Pseudo model, 近似模型 Pseudosigma, 伪标准差Purposive sling, 有目的抽样 QR deposition, QR 分解Quadratic appro_imation, 二次近似 Qualitative classification, 属性分类Qualitative method, 定性方法 Quantile-quantile plot, 分位数-分位数图/Q-Q 图 Quantitative analysis, 定量分析Quartile, 四分位数 Quick Cluster, 快速聚类Radi_ sort, 基数排序 Random allocation, 随机化分组Random blocks design, 随机区组设计 Random event, 随机事件Randomization, 随机化 Range, 极差/全距Rank correlation, 等级相关 Rank sum test, 秩和检验Rank test, 秩检验 Ranked data, 等级资料Rate, 比率 Ratio, 比例Raw data, 原始资料 Raw residual, 原始残差Reciprocal, 倒数 Reducing dimensions, 降维Region of acceptance, 接受域 Regression coefficient, 回归系数Regression sum of square, 回归平方和 Relative dispersion, 相对离散度Relative number, 相对数 Reliability, 可靠性Reparametrization, 重新设置参数 Replication, 重复Report Summaries, 报告摘要 Residual sum of square, 剩余平方和 Resistance, 耐抗性 R-estimator of location, 位置R 估计量R-estimator of scale, 尺度 R 估计量Retrospective study, 回顾性调查 Rotation, 旋转Row, 行 Row factor, 行因素Sle, 样本Sleregression coefficient, 样本回归系数 Sle size, 样本量Sle standard deviation, 样本标准差 Sling error, 抽样误差SAS(Statistical analysis system ), SAS 统计软件包Scale, 尺度/量表Scatter diagram, 散点图 Schematic plot, 示意图/简图Second derivative, 二阶导数 Second principal ponent, 第二主成分SEM (Structural equation modeling), 结构化方程模型Sequential analysis, 贯序分析Sequential data set, 顺序数据集 Sequential design, 贯序设计Sequential method, 贯序法 Sequential test, 贯序检验法Sigmoid curve, S 形曲线 Sign test, 符号检验Signed rank, 符号秩 Significance test, 显著性检验Significant figure, 有效数字 Simple cluster sling, 简单整群抽样 Simple correlation, 简单相关Simple random sling, 简单随机抽样 Simple regression, 简单回归simple table, 简单表 Single-valued estimate, 单值估计Singular matri_, 奇异矩阵 Skewed distribution, 偏斜分布Skewness, 偏度 Slash distribution, 斜线分布Smirnov test, 斯米尔诺夫检验Spearman rank correlation, 斯皮尔曼等级相关 Specific factor, 特殊因子Specific factor variance, 特殊因子方差 Spherical distribution, 球型正态分布 SPSS(Statistical package for the social science), SPSS 统计软件包 Standard deviation, 标准差Standard error, 标准误 Standard error of difference, 差别的标准误 Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误 Standard normal distribution, 标准正态分布 Standardization, 标准化Starting value, 起始值 Statistic, 统计量Statistical control, 统计控制 Statistical graph, 统计图Statistical inference, 统计推断 Statistical table, 统计表Steepest descent, 最速下降法 Stem and leaf display, 茎叶图Step factor, 步长因子 Stepwise regression, 逐步回归Storage, 存 Strata, 层（复数）Stratified sling, 分层抽样 Stratified sling, 分层抽样Studentized residual, 学生化残差/t 化残差 Sufficient statistic, 充分统计量Sum of products, 积和 Sum of squares, 离差平方和Sum of squares about regression, 回归平方和 Sum of squares between groups, 组间平方和 Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查 Survival, 生存分析Survival rate, 生存率 Symmetry, 对称Systematic error, 系统误差 Systematic sling, 系统抽样Tags, 标签 Tail area, 尾部面积Tail length, 尾长 Tail weight, 尾重Target distribution, 目标分布 Taylor series, 泰勒级数Tendency of dispersion, 离散趋势 Testing of hypotheses, 假设检验Theoretical frequency, 理论频数 Time series, 时间序列Tolerance interval, 容忍区间 Total sum of square, 总平方和Total variation, 总变异 Transformation, 转换Treatment, 处理 Trend, 趋势Trend of percentage, 百分比趋势 Trial, 试验Trial and error method, 试错法 Two sided test, 双向检验Two-stage least squares, 二阶最小平方 Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析 Type I error, 一类错误/α错误Type II error, 二类错误/β错误 UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计 Unconstrained nonlinear regression , 无约束非线性回归 Unequal subclass number, 不等次级组含量 Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计 Upper limit, 上限Upward rank, 升秩 Validity, 有效性VARP (Variance ponent estimation), 方差元素估计Variability, 变异性Variable, 变量 Variance, 方差Variation, 变异 Varima_ orthogonal rotation, 方差最大正交旋转 W test, W 检验Weibull distribution, 威布尔分布 Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran 检验Weighted linear regression method, 加权直线回归 Weighted mean, 加权平均数Weighted mean square, 加权平均方差 Weighted sum of square, 加权平方和 Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W 估计量W-estimation of location, 位置 W 估计量 Width, 宽度Wilco_on paired test, 威斯康星配对法/配对符号秩和检验 Z test, Z 检验Zero correlation, 零相关 Z-transformation, Z 变换。
英语专业八级考试TEM-8阅读理解练习册（1）(英语专业2012级)UNIT 1Text AEvery minute of every day, what ecologist生态学家James Carlton calls a global ―conveyor belt‖, redistributes ocean organisms生物.It’s planetwide biological disruption生物的破坏that scientists have barely begun to understand.Dr. Carlton —an oceanographer at Williams College in Williamstown,Mass.—explains that, at any given moment, ―There are several thousand marine species traveling… in the ballast water of ships.‖ These creatures move from coastal waters where they fit into the local web of life to places where some of them could tear that web apart. This is the larger dimension of the infamous无耻的，邪恶的invasion of fish-destroying, pipe-clogging zebra mussels有斑马纹的贻贝.Such voracious贪婪的invaders at least make their presence known. What concerns Carlton and his fellow marine ecologists is the lack of knowledge about the hundreds of alien invaders that quietly enter coastal waters around the world every day. Many of them probably just die out. Some benignly亲切地，仁慈地—or even beneficially — join the local scene. But some will make trouble.In one sense, this is an old story. Organisms have ridden ships for centuries. They have clung to hulls and come along with cargo. What’s new is the scale and speed of the migrations made possible by the massive volume of ship-ballast water压载水— taken in to provide ship stability—continuously moving around the world…Ships load up with ballast water and its inhabitants in coastal waters of one port and dump the ballast in another port that may be thousands of kilometers away. A single load can run to hundreds of gallons. Some larger ships take on as much as 40 million gallons. The creatures that come along tend to be in their larva free-floating stage. When discharged排出in alien waters they can mature into crabs, jellyfish水母, slugs鼻涕虫，蛞蝓, and many other forms.Since the problem involves coastal species, simply banning ballast dumps in coastal waters would, in theory, solve it. Coastal organisms in ballast water that is flushed into midocean would not survive. Such a ban has worked for North American Inland Waterway. But it would be hard to enforce it worldwide. Heating ballast water or straining it should also halt the species spread. But before any such worldwide regulations were imposed, scientists would need a clearer view of what is going on.The continuous shuffling洗牌of marine organisms has changed the biology of the sea on a global scale. It can have devastating effects as in the case of the American comb jellyfish that recently invaded the Black Sea. It has destroyed that sea’s anchovy鳀鱼fishery by eating anchovy eggs. It may soon spread to western and northern European waters.The maritime nations that created the biological ―conveyor belt‖ should support a coordinated international effort to find out what is going on and what should be done about it. (456 words)1.According to Dr. Carlton, ocean organism‟s are_______.A.being moved to new environmentsB.destroying the planetC.succumbing to the zebra musselD.developing alien characteristics2.Oceanographers海洋学家are concerned because_________.A.their knowledge of this phenomenon is limitedB.they believe the oceans are dyingC.they fear an invasion from outer-spaceD.they have identified thousands of alien webs3.According to marine ecologists, transplanted marinespecies____________.A.may upset the ecosystems of coastal watersB.are all compatible with one anotherC.can only survive in their home watersD.sometimes disrupt shipping lanes4.The identified cause of the problem is_______.A.the rapidity with which larvae matureB. a common practice of the shipping industryC. a centuries old speciesD.the world wide movement of ocean currents5.The article suggests that a solution to the problem__________.A.is unlikely to be identifiedB.must precede further researchC.is hypothetically假设地，假想地easyD.will limit global shippingText BNew …Endangered‟ List Targets Many US RiversIt is hard to think of a major natural resource or pollution issue in North America today that does not affect rivers.Farm chemical runoff残渣, industrial waste, urban storm sewers, sewage treatment, mining, logging, grazing放牧,military bases, residential and business development, hydropower水力发电,loss of wetlands. The list goes on.Legislation like the Clean Water Act and Wild and Scenic Rivers Act have provided some protection, but threats continue.The Environmental Protection Agency (EPA) reported yesterday that an assessment of 642,000 miles of rivers and streams showed 34 percent in less than good condition. In a major study of the Clean Water Act, the Natural Resources Defense Council last fall reported that poison runoff impairs损害more than 125,000 miles of rivers.More recently, the NRDC and Izaak Walton League warned that pollution and loss of wetlands—made worse by last year’s flooding—is degrading恶化the Mississippi River ecosystem.On Tuesday, the conservation group保护组织American Rivers issued its annual list of 10 ―endangered‖ and 20 ―threatened‖ rivers in 32 states, the District of Colombia, and Canada.At the top of the list is the Clarks Fork of the Yellowstone River, whereCanadian mining firms plan to build a 74-acre英亩reservoir水库，蓄水池as part of a gold mine less than three miles from Yellowstone National Park. The reservoir would hold the runoff from the sulfuric acid 硫酸used to extract gold from crushed rock.―In the event this tailings pond failed, the impact to th e greater Yellowstone ecosystem would be cataclysmic大变动的，灾难性的and the damage irreversible不可逆转的.‖ Sen. Max Baucus of Montana, chairman of the Environment and Public Works Committee, wrote to Noranda Minerals Inc., an owner of the ― New World Mine‖.Last fall, an EPA official expressed concern about the mine and its potential impact, especially the plastic-lined storage reservoir. ― I am unaware of any studies evaluating how a tailings pond尾矿池，残渣池could be maintained to ensure its structural integrity forev er,‖ said Stephen Hoffman, chief of the EPA’s Mining Waste Section. ―It is my opinion that underwater disposal of tailings at New World may present a potentially significant threat to human health and the environment.‖The results of an environmental-impact statement, now being drafted by the Forest Service and Montana Department of State Lands, could determine the mine’s future…In its recent proposal to reauthorize the Clean Water Act, the Clinton administration noted ―dramatically improved water quality since 1972,‖ when the act was passed. But it also reported that 30 percent of riverscontinue to be degraded, mainly by silt泥沙and nutrients from farm and urban runoff, combined sewer overflows, and municipal sewage城市污水. Bottom sediments沉积物are contaminated污染in more than 1,000 waterways, the administration reported in releasing its proposal in January. Between 60 and 80 percent of riparian corridors (riverbank lands) have been degraded.As with endangered species and their habitats in forests and deserts, the complexity of ecosystems is seen in rivers and the effects of development----beyond the obvious threats of industrial pollution, municipal waste, and in-stream diversions改道to slake消除the thirst of new communities in dry regions like the Southwes t…While there are many political hurdles障碍ahead, reauthorization of the Clean Water Act this year holds promise for US rivers. Rep. Norm Mineta of California, who chairs the House Committee overseeing the bill, calls it ―probably the most important env ironmental legislation this Congress will enact.‖ (553 words)6.According to the passage, the Clean Water Act______.A.has been ineffectiveB.will definitely be renewedC.has never been evaluatedD.was enacted some 30 years ago7.“Endangered” rivers are _________.A.catalogued annuallyB.less polluted than ―threatened rivers‖C.caused by floodingD.adjacent to large cities8.The “cataclysmic” event referred to in paragraph eight would be__________.A. fortuitous偶然的，意外的B. adventitious外加的，偶然的C. catastrophicD. precarious不稳定的，危险的9. The owners of the New World Mine appear to be______.A. ecologically aware of the impact of miningB. determined to construct a safe tailings pondC. indifferent to the concerns voiced by the EPAD. willing to relocate operations10. The passage conveys the impression that_______.A. Canadians are disinterested in natural resourcesB. private and public environmental groups aboundC. river banks are erodingD. the majority of US rivers are in poor conditionText CA classic series of experiments to determine the effects ofoverpopulation on communities of rats was reported in February of 1962 in an article in Scientific American. The experiments were conducted by a psychologist, John B. Calhoun and his associates. In each of these experiments, an equal number of male and female adult rats were placed in an enclosure and given an adequate supply of food, water, and other necessities. The rat populations were allowed to increase. Calhoun knew from experience approximately how many rats could live in the enclosures without experiencing stress due to overcrowding. He allowed the population to increase to approximately twice this number. Then he stabilized the population by removing offspring that were not dependent on their mothers. He and his associates then carefully observed and recorded behavior in these overpopulated communities. At the end of their experiments, Calhoun and his associates were able to conclude that overcrowding causes a breakdown in the normal social relationships among rats, a kind of social disease. The rats in the experiments did not follow the same patterns of behavior as rats would in a community without overcrowding.The females in the rat population were the most seriously affected by the high population density: They showed deviant异常的maternal behavior; they did not behave as mother rats normally do. In fact, many of the pups幼兽，幼崽, as rat babies are called, died as a result of poor maternal care. For example, mothers sometimes abandoned their pups,and, without their mothers' care, the pups died. Under normal conditions, a mother rat would not leave her pups alone to die. However, the experiments verified that in overpopulated communities, mother rats do not behave normally. Their behavior may be considered pathologically 病理上，病理学地diseased.The dominant males in the rat population were the least affected by overpopulation. Each of these strong males claimed an area of the enclosure as his own. Therefore, these individuals did not experience the overcrowding in the same way as the other rats did. The fact that the dominant males had adequate space in which to live may explain why they were not as seriously affected by overpopulation as the other rats. However, dominant males did behave pathologically at times. Their antisocial behavior consisted of attacks on weaker male,female, and immature rats. This deviant behavior showed that even though the dominant males had enough living space, they too were affected by the general overcrowding in the enclosure.Non-dominant males in the experimental rat communities also exhibited deviant social behavior. Some withdrew completely; they moved very little and ate and drank at times when the other rats were sleeping in order to avoid contact with them. Other non-dominant males were hyperactive; they were much more active than is normal, chasing other rats and fighting each other. This segment of the rat population, likeall the other parts, was affected by the overpopulation.The behavior of the non-dominant males and of the other components of the rat population has parallels in human behavior. People in densely populated areas exhibit deviant behavior similar to that of the rats in Calhoun's experiments. In large urban areas such as New York City, London, Mexican City, and Cairo, there are abandoned children. There are cruel, powerful individuals, both men and women. There are also people who withdraw and people who become hyperactive. The quantity of other forms of social pathology such as murder, rape, and robbery also frequently occur in densely populated human communities. Is the principal cause of these disorders overpopulation? Calhoun’s experiments suggest that it might be. In any case, social scientists and city planners have been influenced by the results of this series of experiments.11. Paragraph l is organized according to__________.A. reasonsB. descriptionC. examplesD. definition12．Calhoun stabilized the rat population_________.A. when it was double the number that could live in the enclosure without stressB. by removing young ratsC. at a constant number of adult rats in the enclosureD. all of the above are correct13.W hich of the following inferences CANNOT be made from theinformation inPara. 1?A. Calhoun's experiment is still considered important today.B. Overpopulation causes pathological behavior in rat populations.C. Stress does not occur in rat communities unless there is overcrowding.D. Calhoun had experimented with rats before.14. Which of the following behavior didn‟t happen in this experiment?A. All the male rats exhibited pathological behavior.B. Mother rats abandoned their pups.C. Female rats showed deviant maternal behavior.D. Mother rats left their rat babies alone.15. The main idea of the paragraph three is that __________.A. dominant males had adequate living spaceB. dominant males were not as seriously affected by overcrowding as the otherratsC. dominant males attacked weaker ratsD. the strongest males are always able to adapt to bad conditionsText DThe first mention of slavery in the statutes法令，法规of the English colonies of North America does not occur until after 1660—some forty years after the importation of the first Black people. Lest we think that existed in fact before it did in law, Oscar and Mary Handlin assure us, that the status of B lack people down to the 1660’s was that of servants. A critique批判of the Handlins’ interpretation of why legal slavery did not appear until the 1660’s suggests that assumptions about the relation between slavery and racial prejudice should be reexamined, and that explanation for the different treatment of Black slaves in North and South America should be expanded.The Handlins explain the appearance of legal slavery by arguing that, during the 1660’s, the position of white servants was improving relative to that of black servants. Thus, the Handlins contend, Black and White servants, heretofore treated alike, each attained a different status. There are, however, important objections to this argument. First, the Handlins cannot adequately demonstrate that t he White servant’s position was improving, during and after the 1660’s; several acts of the Maryland and Virginia legislatures indicate otherwise. Another flaw in the Handlins’ interpretation is their assumption that prior to the establishment of legal slavery there was no discrimination against Black people. It is true that before the 1660’s Black people were rarely called slaves. But this shouldnot overshadow evidence from the 1630’s on that points to racial discrimination without using the term slavery. Such discrimination sometimes stopped short of lifetime servitude or inherited status—the two attributes of true slavery—yet in other cases it included both. The Handlins’ argument excludes the real possibility that Black people in the English colonies were never treated as the equals of White people.The possibility has important ramifications后果，影响.If from the outset Black people were discriminated against, then legal slavery should be viewed as a reflection and an extension of racial prejudice rather than, as many historians including the Handlins have argued, the cause of prejudice. In addition, the existence of discrimination before the advent of legal slavery offers a further explanation for the harsher treatment of Black slaves in North than in South America. Freyre and Tannenbaum have rightly argued that the lack of certain traditions in North America—such as a Roman conception of slavery and a Roman Catholic emphasis on equality— explains why the treatment of Black slaves was more severe there than in the Spanish and Portuguese colonies of South America. But this cannot be the whole explanation since it is merely negative, based only on a lack of something. A more compelling令人信服的explanation is that the early and sometimes extreme racial discrimination in the English colonies helped determine the particular nature of the slavery that followed. (462 words)16. Which of the following is the most logical inference to be drawn from the passage about the effects of “several acts of the Maryland and Virginia legislatures” (Para.2) passed during and after the 1660‟s?A. The acts negatively affected the pre-1660’s position of Black as wellas of White servants.B. The acts had the effect of impairing rather than improving theposition of White servants relative to what it had been before the 1660’s.C. The acts had a different effect on the position of white servants thandid many of the acts passed during this time by the legislatures of other colonies.D. The acts, at the very least, caused the position of White servants toremain no better than it had been before the 1660’s.17. With which of the following statements regarding the status ofBlack people in the English colonies of North America before the 1660‟s would the author be LEAST likely to agree?A. Although black people were not legally considered to be slaves,they were often called slaves.B. Although subject to some discrimination, black people had a higherlegal status than they did after the 1660’s.C. Although sometimes subject to lifetime servitude, black peoplewere not legally considered to be slaves.D. Although often not treated the same as White people, black people,like many white people, possessed the legal status of servants.18. According to the passage, the Handlins have argued which of thefollowing about the relationship between racial prejudice and the institution of legal slavery in the English colonies of North America?A. Racial prejudice and the institution of slavery arose simultaneously.B. Racial prejudice most often the form of the imposition of inheritedstatus, one of the attributes of slavery.C. The source of racial prejudice was the institution of slavery.D. Because of the influence of the Roman Catholic Church, racialprejudice sometimes did not result in slavery.19. The passage suggests that the existence of a Roman conception ofslavery in Spanish and Portuguese colonies had the effect of _________.A. extending rather than causing racial prejudice in these coloniesB. hastening the legalization of slavery in these colonies.C. mitigating some of the conditions of slavery for black people in these coloniesD. delaying the introduction of slavery into the English colonies20. The author considers the explanation put forward by Freyre andTannenbaum for the treatment accorded B lack slaves in the English colonies of North America to be _____________.A. ambitious but misguidedB. valid有根据的but limitedC. popular but suspectD. anachronistic过时的，时代错误的and controversialUNIT 2Text AThe sea lay like an unbroken mirror all around the pine-girt, lonely shores of Orr’s Island. Tall, kingly spruce s wore their regal王室的crowns of cones high in air, sparkling with diamonds of clear exuded gum流出的树胶; vast old hemlocks铁杉of primeval原始的growth stood darkling in their forest shadows, their branches hung with long hoary moss久远的青苔;while feathery larches羽毛般的落叶松,turned to brilliant gold by autumn frosts, lighted up the darker shadows of the evergreens. It was one of those hazy朦胧的, calm, dissolving days of Indian summer, when everything is so quiet that the fainest kiss of the wave on the beach can be heard, and white clouds seem to faint into the blue of the sky, and soft swathing一长条bands of violet vapor make all earth look dreamy, and give to the sharp, clear-cut outlines of the northern landscape all those mysteries of light and shade which impart such tenderness to Italian scenery.The funeral was over,--- the tread鞋底的花纹/ 踏of many feet, bearing the heavy burden of two broken lives, had been to the lonely graveyard, and had come back again,--- each footstep lighter and more unconstrained不受拘束的as each one went his way from the great old tragedy of Death to the common cheerful of Life.The solemn black clock stood swaying with its eternal ―tick-tock, tick-tock,‖ in the kitchen of the brown house on Orr’s Island. There was there that sense of a stillness that can be felt,---such as settles down on a dwelling住处when any of its inmates have passed through its doors for the last time, to go whence they shall not return. The best room was shut up and darkened, with only so much light as could fall through a little heart-shaped hole in the window-shutter,---for except on solemn visits, or prayer-meetings or weddings, or funerals, that room formed no part of the daily family scenery.The kitchen was clean and ample, hearth灶台, and oven on one side, and rows of old-fashioned splint-bottomed chairs against the wall. A table scoured to snowy whiteness, and a little work-stand whereon lay the Bible, the Missionary Herald, and the Weekly Christian Mirror, before named, formed the principal furniture. One feature, however, must not be forgotten, ---a great sea-chest水手用的储物箱,which had been the companion of Zephaniah through all the countries of the earth. Old, and battered破旧的，磨损的, and unsightly难看的it looked, yet report said that there was good store within which men for the most part respect more than anything else; and, indeed it proved often when a deed of grace was to be done--- when a woman was suddenly made a widow in a coast gale大风，狂风, or a fishing-smack小渔船was run down in the fogs off the banks, leaving in some neighboring cottage a family of orphans,---in all such cases, the opening of this sea-chest was an event of good omen 预兆to the bereaved丧亲者;for Zephaniah had a large heart and a large hand, and was apt有…的倾向to take it out full of silver dollars when once it went in. So the ark of the covenant约柜could not have been looked on with more reverence崇敬than the neighbours usually showed to Captain Pennel’s sea-chest.1. The author describes Orr‟s Island in a(n)______way.A.emotionally appealing, imaginativeB.rational, logically preciseC.factually detailed, objectiveD.vague, uncertain2.According to the passage, the “best room”_____.A.has its many windows boarded upB.has had the furniture removedC.is used only on formal and ceremonious occasionsD.is the busiest room in the house3.From the description of the kitchen we can infer that thehouse belongs to people who_____.A.never have guestsB.like modern appliancesC.are probably religiousD.dislike housework4.The passage implies that_______.A.few people attended the funeralB.fishing is a secure vocationC.the island is densely populatedD.the house belonged to the deceased5.From the description of Zephaniah we can see thathe_________.A.was physically a very big manB.preferred the lonely life of a sailorC.always stayed at homeD.was frugal and saved a lotText BBasic to any understanding of Canada in the 20 years after the Second World War is the country' s impressive population growth. For every three Canadians in 1945, there were over five in 1966. In September 1966 Canada's population passed the 20 million mark. Most of this surging growth came from natural increase. The depression of the 1930s and the war had held back marriages, and the catching-up process began after 1945. The baby boom continued through the decade of the 1950s, producing a population increase of nearly fifteen percent in the five years from 1951 to 1956. This rate of increase had been exceeded only once before in Canada's history, in the decade before 1911 when the prairies were being settled. Undoubtedly, the good economic conditions of the 1950s supported a growth in the population, but the expansion also derived from a trend toward earlier marriages and an increase in the average size of families; In 1957 the Canadian birth rate stood at 28 per thousand, one of the highest in the world. After the peak year of 1957, thebirth rate in Canada began to decline. It continued falling until in 1966 it stood at the lowest level in 25 years. Partly this decline reflected the low level of births during the depression and the war, but it was also caused by changes in Canadian society. Young people were staying at school longer, more women were working; young married couples were buying automobiles or houses before starting families; rising living standards were cutting down the size of families. It appeared that Canada was once more falling in step with the trend toward smaller families that had occurred all through theWestern world since the time of the Industrial Revolution. Although the growth in Canada’s population had slowed down by 1966 (the cent), another increase in the first half of the 1960s was only nine percent), another large population wave was coming over the horizon. It would be composed of the children of the children who were born during the period of the high birth rate prior to 1957.6. What does the passage mainly discuss?A. Educational changes in Canadian society.B. Canada during the Second World War.C. Population trends in postwar Canada.D. Standards of living in Canada.7. According to the passage, when did Canada's baby boom begin?A. In the decade after 1911.B. After 1945.C. During the depression of the 1930s.D. In 1966.8. The author suggests that in Canada during the 1950s____________.A. the urban population decreased rapidlyB. fewer people marriedC. economic conditions were poorD. the birth rate was very high9. When was the birth rate in Canada at its lowest postwar level?A. 1966.B. 1957.C. 1956.D. 1951.10. The author mentions all of the following as causes of declines inpopulation growth after 1957 EXCEPT_________________.A. people being better educatedB. people getting married earlierC. better standards of livingD. couples buying houses11.I t can be inferred from the passage that before the IndustrialRevolution_______________.A. families were largerB. population statistics were unreliableC. the population grew steadilyD. economic conditions were badText CI was just a boy when my father brought me to Harlem for the first time, almost 50 years ago. We stayed at the hotel Theresa, a grand brick structure at 125th Street and Seventh avenue. Once, in the hotel restaurant, my father pointed out Joe Louis. He even got Mr. Brown, the hotel manager, to introduce me to him, a bit punchy强力的but still champ焦急as fast as I was concerned.Much has changed since then. Business and real estate are booming. Some say a new renaissance is under way. Others decry责难what they see as outside forces running roughshod肆意践踏over the old Harlem. New York meant Harlem to me, and as a young man I visited it whenever I could. But many of my old haunts are gone. The Theresa shut down in 1966. National chains that once ignored Harlem now anticipate yuppie money and want pieces of this prime Manhattan real estate. So here I am on a hot August afternoon, sitting in a Starbucks that two years ago opened a block away from the Theresa, snatching抓取，攫取at memories between sips of high-priced coffee. I am about to open up a piece of the old Harlem---the New York Amsterdam News---when a tourist。
审计的专业术语中英对照汇总2008-10-14四大”会计师事务所：普华永道Princewater - houseCoopers安永Ernst & You ng毕马威KPMG德勤Deloitte Touche Tohmatsu安达信Arthur Anderson安然Enron世通worldcom国际机构的名称：：国际会计师联合会IFAC国际会计师联合会下设的国际审计和鉴证准则理事会IAASB美国注册会计师协会AICPA中国注册会计师协会CICPA审计audit内部审计internal audit政府审计public sector audit账项基础审计acco un ti ng nu mber-based audit风险导向审计方法risk-orie nted audit approach其他鉴证业务audit related services审阅业务review有限责任公司制limited liability compa ni es, LLCs有限责任合伙制limited liability part nerships, LLPs注册会计师职业道德规范code of ethics for professi onal accou ntantsRules of professi onal con duct独立independence客观objectivity公正integrity专业胜任能力professi onal compete nee应有关注due care保密con fide ntiality con fide nee职业行为professi onal conduct技术准贝U technical standards保持实质上的独立和形式上的独立The member is, and is see n to be in depe ndent费用fee佣金commissi on经济利益interest经济利益的冲突conflicts of in terest舞弊fraud: refers to intentional acts which may involve the falsification of documents and records, the misappropriation of assets, or misapplication of accounting policies.差令错error: refers to the unintentional misapplication of accounting policies, oversights or misi nterpretati ons of fact and clerical errors.更换会计师事务所Chan ges in professi onal appo in tme nts国际趋同global con verge nee /intern ati onal con verge nee鉴证业务assuranee services全面质量管理quality control of auditEnforce the ethical guida nee注册会计师的法律责任Professio nal respo nsibility深口袋"理论deep-pocket theory仓U新会计处理creative acco un ti ng诉讼爆炸litigation explosion违约breach the con tract过失negligeneeMisc on duct欺诈cheat / illegal acts审计目标audit objectives怀疑态度suspend财务报表认定：finan cial stateme nt asserti ons存在existenee权利与义务rights and obligati ons发生occurrenee完整性completeness准确性和计价measureme nt and valuati on分类和可理解性classificati on and un dersta ndabilityprese ntatio n and disclosure财务报表循环cyclesSales and receivables cyclePurchases and payables cycleWages and salaries cyclePetty cash cycleInven tory record ing cycle截止cut-off审计任务约定书the letter of en gageme nt管理层声明书report of the directors ' responsibilities for the financial statement审计证据audit evidenee审计工作底稿audit work ing paper审计记录audit records计划工作pla nning重要性material: in formatio n is material if its omissi on or misstateme ntcould in flue nee theecono mic decisi ons of users take n on the basis of the finan cial stateme nts.审计风险audit risk检查风险detection risk重大错报风险risk of material misstateme nt in audit report风险评估risk evaluation分析复核程序an alytical review procedures内部控制in ternal co ntrol局限性limitation控制环境control environment信息系统与沟通in formati on system and com muni cati on符合性测试complia nee test控制测试control test报表层次重大错报material misstateme nt on level of finan cial stateme nt认定层次重大错报material misstateme nt on level of asserti on实质性程序substa ntial procedures舞弊fraud审计扌由样sampling抽样风险sampling risk非抽样风险non-sampling risk统计扌由样statistical sampling非统计抽样non-statistical sampli ng销售与收款循环审计Sales and receivables cycle采购与付款循环审计Purchases and payables cycle监盘physical inspection筹资与投资循环审计In vestme nt and finance cycle货币资金审计Audit of mon etary assets完成审计工作finish the audit work期初余额opening balanee期后事项events after the balanee sheet date或有事项con ti ngent eve ns试算平衡表trail balanee审计报告Audit report审计报告的要素标题title收件人receiver弓I言段introduction管理层对财务报表的责任段man agemen' s respon sibility for the finan cial stateme nts注册会计师的责任段auditor ' s responsibility审计意见段opi nio n注册会计师的监管和盖章auditor ' s sigpture会计师事务所的名称、地址和盖章auditor ' s address报告日期date of the Auditor ' s report无保留意见unq ualified audit report非无保留意见modified audit report保留意见qualified opinion无法表示意见disclaimer否定意见adverse。
总第108期PSYCHOLOGI C AL EXP LORATI O N第4期效度概化的理论研究述评3杨建锋1,王重鸣2(1.江西财经大学工商管理学院,南昌330013;2.浙江大学管理学院,杭州310058)摘 要:效度概化(validity generalizati on:VG)是心理测量理论和元分析的结合体,也是元分析在人事测评领域的重要应用。
它深刻地挑战了人事测评效度的情景特异论,在工业与组织心理学的发展历程当中具有里程碑意义。
该文系统地介绍了效度概化理论的逻辑思路、主要模型、关键理论语与应用,以及研究趋势。
关键词:效度概化;统计性偏差;元分析;人事测评中图分类号:B841.2 文献标识码:A 文章编号:1003-5184(2008)04-0085-051 引言从上世纪六、七十年代开始,心理测评及选拔领域就一直面临着两个方面的难题:一个是测评工具的效度与被测评对象的工作种类有关;另一个就是在类似情景下,采用类似测评工具对从事类似工作的人员进行测验时,效度波动很大。
于是,当时的工业与组织心理学家(如Gui on和Ghiselli等)就认为:由于在不同情境下看似相同的工作,具有截然不同的本质,所以人事测评的效度(主要指效标效度,下文同)具有情景特异性———同样的人事测评工具在不同的情景下会表现出截然不同的效度。
因此,支持“情景特异论”的研究者就认为:人事测评工具对情景变异非常敏感,每个人事测评研究都应该考察其所用测量工具的效度。
70年代末,研究者开始用效度概化理论来检验“情景特异论”的可靠性[1],发现通过研究设计来控制那些可能会影响效度的因素之后,在不同情景下所得到的效度就会表现出明显的一致性[1]。
该结论对工业与组织心理学来讲是具有里程碑意义的,意味着人事测评不再是一种技术,而是一门科学[1]。
VG(validity generalizati on:效度概化)受到了心理学界的普遍关注,现已成为元分析的三大主要应用领域之一[2]。
a r X i v :a s t r o -p h /9901400v 1 28 J a n 1999Mon.Not.R.Astron.Soc.000,000–000(0000)Printed 1February 2008(MN L A T E X style file v1.4)Statistical characteristics of formation and evolutionof structure in the universe.M.Demia´n ski 1,2& A.G.Doroshkevich 3,41Institute of Theoretical Physics,University of Warsaw,00-681Warsaw,Poland 2Department of Astronomy,Williams College,Williamstown,MA 01267,USA3Theoretical Astrophysics Center,Juliane Maries Vej 30,DK-2100Copenhagen Ø,Denmark4Keldysh Institute of Applied Mathematics,Russian Academy of Sciences,125047Moscow,RussiaAccepted ...,Received 1998October ...;in original form 1998October 13ABSTRACTAn approximate statistical description of the formation and evolution of structure of the universe based on the Zel’dovich theory of gravitational instability is proposed.It is found that the evolution of DM structure shows features of self-similarity and the main structure characteristics can be expressed through the parameters of initial power spectrum and cosmological model.For the CDM-like power spectrum and suitable parameters of the cosmological model the effective matter compression reaches the observed scales R wall ∼20–25h −1Mpc with the typical mean separation of wall-like elements D SLSS ∼50–70h −1Mpc.This description can be directly applied to the deep pencil beam galactic surveys and absorption spectra of quasars.For larger 3D catalogs and simulations it can be applied to results obtained with the core-sampling analysis.It is shown that the interaction of large and small scale perturbations modulates the creation rate of early Zel’dovich pancakes and generates bias on the SLSS scale.For suitable parameters of the cosmological model and reheating process this bias can essentially improve the characteristics of simulated structure of the universe.The models with 0.3≤Ωm ≤0.5give the best description of the observed struc-ture parameters.The influence of low mass ”warm”dark matter particles,such as a massive neutrino,will extend the acceptable range of Ωm and h .Key words:cosmology:large-scale structure of the Universe —galaxies:clusters:general –theory.1INTRODUCTIONOver the past decade the large maps of the spatial galaxy distribution have been prepared and the unexpectedly com-plicated character of this distribution was established.The structure predicted by the Zel’dovich theory of gravitational instability (Zel’dovich 1970,1978)was found already in the first wedge diagrams (Gregory &Thompson 1978)and now the Large Scale Structure (LSS)is seen in many obser-vational catalogs,such as the CfA (de Lapparent,Geller &Huchra 1987;Ramella,Geller &Huchra 1992),the SRSS (da Costa et al.1988)and in the Las Campanas Redshift Sur-vey (Shectman et al.1996,hereafter LCRS).The observed high concentration of galaxies within the wall-like structure elements such as the Great Attractor (Dressler et al.1987),and the Great Wall (de Lapparent,Geller &Huchra 1988)and the existence of extended under dense regions similar to the Great Void (Kirshner et al.1983)put in the forefront the investigation of the Super Large Scale Structure (SLSS).Now the SLSS is also found in many deep pencil beam red-shift surveys (Broadhurst et al.1990;Willmer et al.1994;Buryak et al.1994;Bellanger &de Lapparent 1995;Cohen et al.1996)as a rich galaxy clumps with the typical sepa-rations in the range of (60–120)h −1Mpc.Here h=H 0/100km/s/Mpc is the dimensionless Hubble constant.Further progress in the statistical description of the LSS &SLSS has been reached with the core-sampling method (Buryak et al.1994)and the Minimal Spanning Tree tech-nique (Barrow,Bhavsar &Sonoda 1985).Recent analy-sis of the LCRS performed by Doroshkevich et al.(1996&1997b,hereafter LCRS1&LCRS2,Doroshkevich et al.1998)revealed some statistical parameters of the wall-like SLSS component such as their typical separation,D SLSS ≈50−60h −1Mpc,and the fraction of galaxies accumulated by the SLSS,which can reach ∼50%.The same analysis indi-cates that formation of richer walls can be roughly described as an asymmetric 2D collapse of regions with a typical size R wall ∼20–25h −1Mpc that is about half of their typicalc0000RAS2Demia´n ski&Doroshkevichseparation.The analysis of Durham/UKST redshift survey confirms these results(Doroshkevich et al.,1999).Earlier similar scales,in the range of(50–100)h−1Mpc,were found only for spatial distribution of clusters of galaxies(see,e.g., Bahcall1988;Einasto et al.1994)and for a few superclusters of galaxies(see,e.g.,Oort1983a,b).Evolution of structure was discussed and simulated many times(see,e.g.,Sahni et al.1994;Doroshkevich et al.1997a,hereafter DFGMM;for references,Sahni&Coles 1995).However,SLSS in the dark matter(DM)distribution similar to that seen in the LCRS was found only recently in a few simulations with the CDM-like power spectrum andΩm h=0.2–0.3,(Cole,Weinberg,Frenk&Ratra1997; Doroshkevich,M¨u ller,Retzalf&Turchaninov1999,here-after DMRT).Hence,for suitable cosmological models the evolution of small initial perturbations results in the SLSS formation.In this paper we present an approximate statistical de-scription of the process of DM structure formation based on the nonlinear Zel’dovich theory.The potential of this ap-proach is limited as the successive consideration of mutual interactions of the small and large scale perturbations be-comes more and more cumbersome.In spite of this it allows us to obtain some interesting results.Thus,it is shown that formation of both LSS and SLSS is a joint process possess-ing some features of self-similarity.The main observed characteristics of LSS and SLSS are expressed through the structure functions of power spectrum and through the typ-ical scales,set by the power spectrum,the time scale,set by the amplitude of perturbation,and the main parameters of cosmological model.One of the most interesting such charac-teristics is the dynamical scale of the nonlinearity defined as the scale of essential DM concentration within high density walls.We show that for the CDM transfer function(Bardeen et al.1986,hereafter BBKS)and Harrison–Zel’dovich pri-mordial power spectrum and for cosmological models with lower matter density this scale of nonlinearity reaches20–30h−1Mpc that is comparable with typical scales of the observed SLSS elements.Simulations(DMRT)show that even in cosmological models with a low matter density the simulated velocity dispersion within the SLSS elements reaches400–700km/s along each principal axis;this exceeds the observed value by a factor of∼1.5–2.Such a large and isotropic velocity dispersion is caused by the disruption of the walls into high density clouds.For smaller matter density of the universe this dispersion decreases but together with the fraction of matter accumulated by the walls.This means that other factors as,for example,the large scale bias in the spatial galaxy distribution relative to the more homogeneous dis-tribution of DM and baryons could be essential for the suc-cessful reproduction of the observed SLSS.Such large scale bias caused by the interaction of small and large scale per-turbations was discussed by Dekel&Silk(1986),and Dekel &Rees(1987),and estimated by Demia´n ski&Doroshke-vich(1999,hereafter Paper I).The interaction of small and large scale perturbations is important during all evolutionary stages.Thus,even dur-ing early evolutionary periods the large scale perturbations modulate the rate of pancake formation.This modulation is seen as an acceleration of the pancake formation within deeper potential wells which later are transformed into the wall-like SLSS elements(Buryak et al.1992;Demia´n ski& Doroshkevich1997;Paper I).Suppression of pancake forma-tion near the peaks of gravitational potential noted by Sahni et al.(1994)is another manifestation of such interactions. During all evolutionary stages these interactions result in the successive merging of individual pancakes.The acceler-ation of pancake disruption,caused by compression of mat-ter within walls,can also be attributed to this interaction. Now it is observed as a high velocity dispersion in simulated SLSS and as differences between the expected and measured mass functions.It was found to be essential even for pan-cakes formed at high redshifts(Miralda-Escude et al.1996). The possible correlation of galaxy morphology with large scale perturbations was discussed by Evrard et al.(1990). All these manifestations of small and large scale interaction are important for the correct comparison and interpretation of simulated and observed matter distribution.Now the modulation of spatial distribution of pancakes formed at high redshifts z≥4can be seen as the large scale bias in the galaxy and DM spatial distribution.This bias can be generated by the combined action of large scale per-turbations and reheating of baryonic component of the uni-verse(see,e.g.,Dekel&Silk1986;Dekel&Rees1987).The reheating was discussed many times during the last thirty years in various aspects(see,e.g.,Sunyaev&Zel’dovich 1972;White&Rees1978;Shapiro,Giroux&Babul1994). Effects of reheating on the process of galaxy formation were discussed as well(see,e.g.,Babul&White1991;Efstathiou 1992;Quinn,Katz&Efstathiou1996).It is also known that under reasonable assumptions about the possible en-ergy sources reheating can occur for relatively small range of redshifts z≈5−10(see,e.g.,Tegmark et al.1997;Baltz et al.1998).If essential concentration of baryons in high density clouds is reached at the same redshifts,the reheat-ing can help to generate bias(Demia´n ski&Doroshkevich 1997;Paper I).In this case further formation of high den-sity baryonic clouds will be significantly depressed,due to reheating,within extended regions observed today as under dense regions between richer walls.Our estimates show that this spatial modulation of the luminous matter distribution may be essential for the interpretation of observations.Numerical simulations are now the best way to repro-duce and to study the joint action of all the pertinent fac-tors together and to obtain more representative descrip-tion of the process of structure formation.Essential progress achieved recently both in the simulations and study of DM and’galaxy’distributions(Governato et al.1998;Jenkins et al.1998;Doroshkevich,Fong&Makarova1998;DMRT; Cole,Hatton,Weinberg&Frenk1998)allows us to follow the structure evolution in a wide range of redshifts and to re-veal differences between DM and galaxy -parison of these results with observations and an approxi-mate theoretical description stimulates further progress in our understanding of evolution of the universe.This paper is organized as follows:In Sect.2main nota-tions are introduced.In Sec.3and4the distribution func-tions of DM pancakes are derived and the interaction of small and large scale perturbations is described that allows us to obtain in Secs.5and6the statistical characteristics of DM structure.In Sec.7the large scale bias is discussed and in Sec.8the dynamical characteristics of walls are found.In Sec.9the theoretical estimates are compared with the avail-c 0000RAS,MNRAS000,000–000Formation and evolution of structure3 able observational and simulated data.We conclude withSec.10where a short discussion of the main results is pre-sented.Some technical details are given in Appendixes I–IV.2STATISTICAL PARAMETERS OFPERTURBATIONS:V ARIANCES ANDTYPICAL SCALESThe simplest characteristics of perturbations are the vari-ances of density and velocity perturbations.For a more de-tailed statistical description of the structure evolution it isnecessary to use also the structure functions.They were in-troduced in Paper I and are briefly described in this Sectionand Appendix I.Here we consider only the SCDM-like powerspectrum but the same approach can be applied for otherspectra as well.Our analysis is based on the Zel’dovich theory whichlinks the Eulerian,r i,and the Lagrangian,q i,coordinatesoffluid elements(particles)by the expressionr i=(1+z)−1[q i−B(z)S i(q)],(2.1)where z denotes the redshift,B(z)describes growth of per-turbations in the linear theory,and the potential vectorS i(q)=∂φ/∂q i characterizes the spatial distribution of per-turbations.The Lagrangian coordinates of a particle,q i,areits unperturbed comoving coordinates.For theflat universe withΩm+ΩΛ=1,Ωm≥0.1,thefunction B(z)can be approximated with a precision betterthen10%by the expression(Paper I)B−3(z)≈1−Ωm+2.2Ωm(1+z)31+1.5Ωmz(2.3)(Zel’dovich&Novikov1983).ForΩm=1,ΩΛ=0bothexpressions give B−1(z)=1+z.The main characteristics of the perturbations are thevariances of densityσ2ρ,displacementσ2s,and componentsof the deformation tensorσ2Dσ2s=12π2 ∞0p(k)k2dk,(2.4)where p(k)is the power spectrum,and k is the comoving wave number.The power spectrum determines also two amplitude in-dependent typical scales,which allow us to describe the pro-cess of structure formation and can be,possibly,estimated from the observed galaxy distribution.For the Harrison–Zel’dovich primordial power spectrum these scales,l0and l c,are defined asl−20= ∞0kT2(k/k0)dk,l2c=5σ2ρ,(2.5)where T2(x)is the transfer function and k0=Ωm h2Mpc−1. For the CDM transfer function(BBKS)the scale l0and the typical masses of DM and baryonic components associated with the scale l0arel0≈6.6(Ωm h)−1 m−2h−1Mpc,(2.6)M0=πΩ2m h4,M(0)b=Ωb√l0 3M0≈0.6·1010M⊙m−220µK a(Ωm,ΩΛ)Mpc,(2.8)a(Ωm,ΩΛ=1−Ωm)=Ω0.215−0.05lnΩmm,a(Ωm,ΩΛ=0)=Ω0.65−0.19lnΩmm.where T Q is the amplitude of quadrupole component of anisotropy of the relic radiation.The time scale of the struc-ture evolution is defined by the functionτ(z)=τ0B(z),(2.9)τ0=σs3l0≈2.73h2Ωm m−220µK a(Ωm,ΩΛ),τ0≈2.73h2Ω1.21m m−220µK ,ΩΛ=1−Ωm,τ0≈2.73h2Ω1.65−0.19lnΩmm m−220µK,ΩΛ=0,Ωm≤1.Further on,as a rule,the dimensionless variables will be used.We will use l0as the unit of length,and<ρ>l0as the unit of surface density.This means also that such dimen-sionless characteristics of a pancake as the size of collapsed slab and resulting surface density of a pancake are identical. Below we will use both terms as well as the term’mass’,m,c 0000RAS,MNRAS000,000–0004Demia´n ski&Doroshkevichto characterize the surface density reached during formation of a pancake.The gravitational potential and displacement are measured in units ofσs l0/√3,respectively.3STATISTICAL CHARACTERISTICS OF PANCAKESIn this section the mass function of Zel’dovich pancakes and its time evolution is given.This can be done using the main equation of Zel’dovich theory(2.1).The mass of compressed matter is measured by the Lagrangian size of compressed slab,q,or by the surface density of pancake,<ρ>q.As it was noted above,both measures are identical in dimen-sionless notation.So,we will use both terms’size’,q,and ’mass’,m,of a pancake to characterize its surface density.Here we do not consider the transversal characteristics of structure elements and cannot discriminate,for example, the central part of a poorer pancake and periphery of richer pancake,if they have the same surface density or mass,m. In this sense our approach gives characteristics similar to that obtained with the core-sampling analysis,pencil beam observations or the distribution of absorption lines in spectra of QSOs.3.1The pancake formationAccording to the relation(2.1)when two particles with dif-ferent Lagrangian coordinates q1and q2meet at the same Eulerian point r a pancake with the surface mass density <ρ>|q1−q2|forms.Here we assume that all particles situ-ated between these two boundary particles are also incorpo-rated into the same pancake.This assumption is also made in the adhesion approach(see,e.g.,Shandarin&Zel’dovich 1989).Formally,this condition can be written asq12=q1−q2=τ·[S(q1)−S(q2)].(3.1) This means that the pancake formation process can be char-acterized by the scalar random functionQ(q12)=q128 1+erf µ(q)2τ 3,(3.3)µ(q)=q2[1−G12(q)].where(see Appendix I&II)µ(q)≈q/2,q0≪q<1,µ(q)≈q/√ln M DM,M q=q30M0≈3.·108M⊙8of matter withQ(q12)≥0is compressed at least in one direction and for∼12π,σ2λ=(13/6−4.5/π)σ2D.As in theZel’dovich theory pancake formation is described by the re-lation B(z)λ1=1(which follows directly from(2.1)),so forthe fraction of compressed matter withλ1≥1/B we havef DM≈1√l0τ−32π (3.5)and forτ≫l c/l0,f DM→1(in the Zel’dovich theory0.92≤f DM≤1).This shows that already during the earlyperiod of nonlinear evolution,atτ≈l c/l0≪1,large frac-tion of matter f DM≥0.9is compressed into low mass pan-cakes.But for the CDM-like power spectrum the descriptionof matter compression through the deformation tensor is ap-propriate only at small scales q≤q0whereas for q≫q0,the correlations between matterflow in orthogonal direc-tions rapidly decrease what can be seen directly from theexpressions for the structure functions given in Appendix I.At larger scales we have to use the more cumbersomedescription discussed above and the estimate(3.3)showsthat at such scales the efficiency of matter integration intostructure elements is only∼0.875(more accurate estimatestaking into account the correlation of displacements lowersthis value to0.79).This limit is reached already at smallτ,for q≪1,that means strong matter concentration withinsmall structure elements.Further evolution does not changethis limit and only redistributes–due to sequential merging–the compressed matter to more and more massive struc-ture elements.Thus,the approximate estimates show that∼21%of matter is subjected to3D compression,∼21%to3Dexpansion,∼29%of matter is subjected to2D compressionand can be accumulated byfilaments and∼29%is subjectedto1D compression and remains in pancakes.The differencebetween estimates(3.3)and(3.5)shows that∼15–20%of matter incorporated in small clouds,with M≤M q,isc 0000RAS,MNRAS000,000–000Formation and evolution of structure5 not accumulated by larger pancakes,with M≥M q,and re-mains distributed between those pancakes.These estimatescan be changed because the Zel’dovich approximation be-comes invalid when strong matter compression is reachedduring pancakes formation.3.2The characteristics of pancake formationThe probability distribution function(PDF)for pancakesformed at the momentτcan be found from(3.3)asN cr(q,τ)=−8dq=62πτdµ√7 ∞0W cr dq,(3.7)<m(τ)>≈4τ2,τ≪1,<m(τ)>≈τ,τ≥1, and the mass distribution is characterized by the functionN(m)cr =62πτqdqΦ µ2τ .(3.8)The rate of formation of pancakes with mass q isNτ=8dτ(q,τ)=62πµ√4√q<∇Q·d r>Φ µ2τ .When l c≪l0it is described by the following(approximate)expression:n(>q)≈3<µr>q0[√3+√qΦ µ2τ ,l c n(>q)≈1.356πµ(q)√32π2<Q22Q33−Q223>√∂q i,Q ij=∂2Qτ2−1+2qτ2−1,(3.12)n0=33qq0 3/2Φµ2τ .The function n31is similar to the standard expression foran isotropic Gaussianfield(BBKS).Thefirst zero of Euler characteristic describes ap-proximately the percolation when separate higher peaksare incorporated into a larger(in the limiting case-in-finite)structure element(Tomita1990;Mecke and Wag-ner1991).The expressions(3.12)show that in the direc-tions orthogonal to q12the percolation takes place at the’moment’τ=µ(q)whereas along q12it occurs later,atτ=µ(q)6Demia´n ski&Doroshkevichdensity of such peaks can be obtained from(3.12),forµ/τ> 1,asl30n pk(>q,τ)=n0µ2τ1,D sep =0.5·erfc(g2/√√τ;D12dqe−0.5g22.(3.15)These relations characterize the parameters of pancakes formed at the momentτunder the condition of a pancake formation at the momentτ1with the size D1and the sepa-ration D sep.The basic relation(3.1)implies that two pancakes with sizes D1and D2and a separation|D sep|≤0.5(D1+D2) merge together and form a single pancake.For larger separa-tions merging of pancakes can also be considered in the same manner as before,but using the Euler position of formed pancaker pan= q1q2r(q)1+z q cent−B(z)∆φ122erfc χ(D1,D2,D sep)2 (3.17)The functionχ(D1,D2,D sep)is given by(III.6).We can ex-tend applicability of the formula(3.17)for small separations by requiring thatW merg(D1,D2,D sep)=1,|D sep|≤0.5(D1+D2).(3.18)4PANCAKE EVOLUTION AND FORMATION OF FILAMENTSSimilar technique can also be used to estimate the transver-sal size,the pancakes compression and/or expansion in transversal directions,and other properties of pancakes.As we are interested in the formation of structure elements with typical sizes q≫q0the local description through the de-formation tensor cannot be used and the imposed condi-tions make even approximate description of pancake evolu-tion quite cumbersome(see,e.g.,Kofman et al.1994).The general tendencies and rough characteristics of this evolu-tion can only be outlined.Thus,for example,we can esti-mate the matter fraction compressed withinfilamentary-like elements and high density clumps as of about50%whereas only∼29%of matter is subjected to1D compression.This estimate implies that larger pancakes could also incorporate an essential fraction offilaments and clumps.The formation offilaments as well as pancakes disrup-tion are stimulated by the growth of density in the course of pancakes compression,and therefore,probably,during early evolutionary stages,filaments represent the most conspicu-ous elements of the structure.As was discussed in Sec.3.3,filaments merge to form a joint ter,when larger pancakes are formed,the evolution of pancakes becomes slower and disruption of pancakes dominates.These expec-tations are consistent with the observed and simulated mat-ter distribution.Thus,the conspicuousfilaments are seen even at z=3(see,e.g.,Governato et al.1998;Jenkins et al. 1998)whereas disrupted walls dominate at small redshifts (LCRS1,LCRS2,DMRT).4.1The characteristics offilament formation Some approximate characteristics offilament distribution can be obtained by considering the formation offilaments as a sequential matter compression along two principal direc-tions.Such two step compression results in formation of highc 0000RAS,MNRAS000,000–000Formation and evolution of structure7 density”ridge”surrounded by a lower density anisotropichalo.In a coordinate system with thefirst and second axesoriented along the directions of maximal and intermediatecompressions this process can be approximately describedby two equations similar to(3.2):Q(q12)=q12/τ,Q(y12)=y12/τf.(4.1)Here vectors q12and y12and functions Q(q12)&Q(y12)describe the deformation along thefirst and second coordi-nate axes respectively and additional conditions introducedin(3.2)are assumed to be fulfilled.As was discussed abovethe matter compression along the second axis is acceleratedby the pancake formation and the functionτf(z)differs fromthat given by(2.9).Bearing in mind these restrictions we will approxi-mately characterize the probability offilament formation,W f cr,for given q&y prior to the’time’τ&τf or forgivenτ&τf with sizes larger then q&y,respectively,asthe probability to have Q(q12)/q12≥Q(y12)/y12≥1/τf,Q(q12)/q12≥1/τ:W f cr(>q,τ;>y,τf)=1−1√8erfc µ(q)2τ 1+erf µ(y)2τf 2.(4.2) The PDF for thefilaments,N f cr,can be found from(4.2)asN(f)cr (q,τ;y,τf)=8dqdµ(y)2τ2−µ(y)√q/2,y≪1,µ(y)≈√2π<m f>√x e−√2(x+1/x)(4.4)ξ=m f8erfc µ(q)2τ 1+erf µ(y)2τf 2.instead of expressions(3.2)and(3.3).The PDF for suchpancakes isN(p)cr(q,τ)= πdµ(q)2τ2 ,0≤q≤∞.(4.5)<m p>=4τ2q≪1.This PDF differs from(3.6)by the form of the functionΦ(x)what decreases the PDF for largerµ/τ.As before,expression(4.5)characterizes pancakes bythe surface mass density of collapsed matter,q.However thepancake surface mass density varies with time after pancakeformation due to transversal compression or expansion thatresults,in particular,in formation offilaments.Even if thesetransversal motions do not lead to such dramatic resultsthey can change drastically the observed surface density ofpancakes.So,the current surface mass density m p=q/s p,where s p describes the variation of pancake surface causedby transversal motions,is a more adequate characteristic ofpancakes.As was discussed above this period of pancake evolutionis not adequately described by the Zel’dovich theory and ourresults become unreliable.To obtain qualitative characteris-tics of influence of these factors we can,for example,describethe variation of pancake’s surface ass p∝(1−τ∗Q(y12)/y12)(1−τ∗Q(z12)/z12).Here vectors y12and z12,and functions Q(y12)&Q(z12),de-scribe the deformation along the second and third coordinateaxes respectively.The functionτ∗differs from that givenby(2.9)and it can depend on transversal motions.Evenso rough consideration shows that the exponential term in(4.5)is eroded,and the resulting PDF becomes power-like:N(m p≪1)∝m−1/2p,N(m p≫1)∝m−2p.(4.6)The pancake disruption accelerates this erosion as well andmakes the PDF more complicated.This discussion shows that slowly evolving pancakeswith slower transversal motions can be separated into aspecial subpopulation for which the surface density changesslowly,m p≈q,and the PDF(4.5)correctly describes thepancake distribution during the essential period of evolution.This subpopulation is singled out by conditions|Q(z12)/z12|≤|Q(y12)/y12|≤ǫ/τ,ǫ<1and the probability of existence of such pancakes is pro-portional toτ−2.This factor describes the disappearance ofsuch pancakes in the course of evolution.This subpopulationcan be however quite rich(see.,discussion in Sec.9).5STATISTICAL CHARACTERISTICS OFDARK MATTER STRUCTURE ELEMENTSResults obtained above allow us tofind the approximatePDF and other characteristics of structure elements.Thestructure element with a size(mass)m is defined as a pan-cake with the size m formed at a momentτthat not mergedwith any other pancake.c 0000RAS,MNRAS000,000–0008Demia´n ski&Doroshkevich5.1Merging of dark matter structure elementsAs before the characteristics of structure element at a mo-mentτare expressed through characteristics of initial per-turbations.The approximate expression for the PDF of structure element can be written in a form similar to the known equation of coagulation:N str(m,τ)=(5.1) ∞dy m0dxN cr(x,τ)N c(m−x,x,y,τ)dW merg(x,m−x,y)dy.The functions N cr,N c&W merg are given by(3.6),(3.15), (3.17)&(3.18).Here thefirst term describes the formation of two pancakes with sizes x&m−x and a separation y and their merging to a pancake with the size m while the second term describes merging of the pancake of size m with another pancake.If the mass exchanged during merging is incorporated into the forming pancake then thefirst term in (5.1)has to be appropriately changed.Here,as thefirst step of investigation,we will use the simpler approximate approach based on the survival proba-bility of a pancake with size m to avoid merging with larger pancakes with sizes x≥m.For the more interesting case of smaller pancakes with q0≪m≤x<1,the most prob-able process is the formation of two pancakes with sizes m&x≥m at a small separation|D sep|≤0.5(x+m)that means,as follows from(3.1),formation of one structure ele-ment with a size x.This process is described by the second term in(5.1).Because in this case the probability of merging quickly decreases for larger separations|D sep|≥0.5(m+x) and the function W c(m,x,D sep)weakly depends on D sep, we will use the approximate expression for the probability of merging,P mrg,P mrg(m,τ)≈2W c m,τ;mτ ,(5.2)P mrg(m,τ)≈erfc µ(m)2 ,m≪1,(5.3) and for the survival probability,P surv,P surv(m,τ)≈1−P mrg(m,τ),(5.4)P surv(m,τ)≈erf µ(m)2 ,m≪1.In spite of the approximate character of this approach,it allows us to obtain reasonable estimates of the expected effi-ciency of merging and of the large scale bias.As it is directly seen from(5.4),forµ(m)≤τ,P surv(m,τ)∝µ(m)τ−1,what characterizes the impact of pancakemerging.Figure1.The PDF of structure elements,N str(m,τ),the mass distribution function,mN str(m,τ),and the fraction of com-pressed matter,f(>m),vs.the masses(sizes)of structure el-ements,m/m m,are plotted forfive moments of time:τ=0.1 (solid line),τ=0.3(dashed line),τ=0.5(dot-dashed line),τ= 0.7(dot-dot-dot-dashed line),τ=2(long dashed line).5.2Statistical characteristics of structureelementsWith this survival probability the approximate PDF for the structure elements,N str(q,τ),can be written as follows:N str(m,τ)∝P surv(m,τ)N cr(m,τ).(5.5) These relations allow us to obtain also the approximate mass distribution function,N(m)str(m,τ),characterizing the distri-bution of compressed matter over the structure elements. For the more interesting case m≪1we haveN str(m,τ)≈242πτdµ√√dmP surv(m,τ)(5.7) =n(>m,τ)P surv(m,τ)+ ∞m dmn(>m,τ)dP surv(m,τ)。
