Spatial Statistics Review
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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 random sampling 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 rank tests 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(Series Bias)类别量表(Nominal Scale) 次级资料(Secondary Data)顺序量表(Ordinal Scale) 抽样架构(Sampling frame)比率量表(Ratio Scale) 集群抽样(Cluster Sampling)连检定法(Run Test) 便利抽样(Convenience Sampling)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-Related Validity)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(Telephone Interview)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(Online Analytical 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 Discovery Absolute 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。
SSCI收录数学心理学学科期刊10种SOCIAL SCIENCES CITATION INDEX - PSYCHOLOGY, MATHEMATICALJOURNAL LISTTotal journals: 101. APPLIED MEASUREMENT IN EDUCATION 《教育实用测度》美国QuarterlyISSN: 0895-7347LAWRENCE ERLBAUM ASSOC INC-TAYLOR & FRANCIS, 325 CHESTNUT STREET, STE 800, PHILADELPHIA, USA, PA, 191062. APPLIED PSYCHOLOGICAL MEASUREMENT 《应用心理检测》美国QuarterlyISSN: 0146-6216SAGE PUBLICATIONS INC, 2455 TELLER RD, THOUSAND OAKS, USA, CA, 913203. BEHAVIOR RESEARCH METHODS 《行为研究方法》美国QuarterlyISSN: 1554-351XPSYCHONOMIC SOC INC, 1710 FORTVIEW RD, AUSTIN, USA, TX, 787044. BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY 《英国数学与统计心理学杂志》英国SemiannualISSN: 0007-1102BRITISH PSYCHOLOGICAL SOC, ST ANDREWS HOUSE, 48 PRINCESS RD EAST, LEICESTER, ENGLAND, LEICS, LE1 7DR5. EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 《教育与心理测量》美国BimonthlyISSN: 0013-1644SAGE PUBLICATIONS INC, 2455 TELLER RD, THOUSAND OAKS, USA, CA, 913206. JOURNAL OF CLASSIFICATION 《分类杂志》美国SemiannualISSN: 0176-4268SPRINGER, 233 SPRING STREET, NEW YORK, USA, NY, 100137. JOURNAL OF EDUCATIONAL MEASUREMENT 《教育测量杂志》英国QuarterlyISSN: 0022-0655BLACKWELL PUBLISHING, 9600 GARSINGTON RD, OXFORD, ENGLAND, OXON, OX4 2DQ8. JOURNAL OF MATHEMATICAL PSYCHOLOGY 《数学心理学杂志》美国BimonthlyISSN: 0022-2496ACADEMIC PRESS INC ELSEVIER SCIENCE, 525 B ST, STE 1900, SAN DIEGO, USA, CA, 92101-44959. PSYCHOMETRIKA 《心理测量学》美国QuarterlyISSN: 0033-3123SPRINGER, 233 SPRING STREET, NEW YORK, USA, NY, 1001310. PSYCHONOMIC BULLETIN & REVIEW 《心理环境通报与评论》美国QuarterlyISSN: 1069-9384PSYCHONOMIC SOC INC, 1710 FORTVIEW RD, AUSTIN, USA, TX, 78704。
·心理卫生评估·困顿感量表中文版测评医学生的效度和信度*龚睿婕1刘景壹1王亦晨2蔡泳3王甦平3(1上海市徐汇区疾病预防控制中心,上海2002372上海交通大学医学院附属瑞金医院,上海2000253上海交通大学医学院,上海200025通信作者:王甦平wangsuping@)【摘要】目的:引进困顿感量表(ES),评价其在医学生群体中的信效度。
方法:选取某医学院校学生1768名,将其随机分半,一半(n=855)进行探索性因子分析,另一半(n=913)进行验证性因子分析;采用病人健康问卷9条目(PHQ-9)检验效标效度。
间隔1个月后,在总样本中选取53名学生进行重测。
结果:探索性因子分析显示量表共16个条目,包含1个公因子,累计方差解释率64.66%,各条目的因子负荷值在0.23 0.77之间;验证性因子分析表明两因子模型拟合情况略优于一因子模型(χ2/df=7.00,RMSEA=0.08,GFI=0.91,CFI=0.95),各因子负荷在0.48 0.89之间。
ES得分与PHQ-9得分呈正相关(ICC=0.44)。
总量表的Cronbachα系数为0.96,2个维度的α系数分别为0.94和0.93;总量表的重测信度为0.83,2个维度的重测信度为0.80、0.83。
结论:困顿感量表中文版在医学生群体有良好的信效度,可以用于评估该群体的困顿感。
【关键词】困顿感量表;医学生;效度;信度中图分类号:B841.7文献标识码:A文章编号:1000-6729(2019)005-0393-05doi:10.3969/j.issn.1000-6729.2019.05.015(中国心理卫生杂志,2019,33(5):393-397.)Validity and reliability of the Chinese vision of theEntrapment Scale in medical studentsGONGRuijie1,LIU Jingyi1,WANG Yichen2,CAI Yong3,WANG Suping3 1Shanghai Xuhui Center for Disease Control and Prevention,Shanghai200237,China2Shanghai Jiao Tong University School of Medicine,Ruijin Hospital,Department of Hospital Infection Control,Shanghai200025,China3School of Medicine,Shanghai Jiao Tong University,Shanghai200025,ChinaCorresponding author:WANG Suping,wangsuping@【Abstract】Objective:To evaluate the validity and reliability of the Chinese vision of the Entrapment Scale (ES)in medical students.Methods:Totally1768medical students were selected.They were randomly allocated into two groups for exploratory factor analysis(n=855)and confirmatory factor analysis(n=913).All samples were assessed in criterion validity with the Patient Health Questionnaire(PHQ-9).One month later,53partici-pants were retested.Results:The exploratory factor analysis extracted1component from16items,and explained64.66%of the total variance.The factor loading of items ranged between0.23-0.77.The confirmatory factor a-nalysis verified that the fitting of the two-factor model was slightly better than that of the one-factor model(χ2/df=7.00,RMSEA=0.08,GFI=0.91,CFI=0.95).The factor loading of items ranged from0.48to0.89.TheES scores were positively correlated with the PHQ-9scores(ICC=0.44).Cronbach'sαcoefficients were0.96 for the total scale and0.83for the test-retest reliability.The internal consistency reliabilities for the2factors were*基金项目:国家自然科学基金———基于IMB模型的跨性别男男性行为者艾滋病高危行为干预策略研究0.94and0.93,and the test-retest reliabilities for the2factors were0.80and0.83.Conclusion:The Chinese vi-sion of the Entrapment Scale has good validity and reliability among Chinese medical students,and it could be used in the evaluation of entrapment.【Key words】Entrapment Scale;medical students;validity;reliability(Chin Ment Health J,2019,33(5):393-397.)困顿感(entrapment)在心理生理学中指想要摆脱威胁或者压力,但是自身没有能力而继续处于被困的一种感觉或个人心理状态[1]。
Value Engineering・1・安徽省区域经济高质量发展综合评价——基于熵权TOPSIS法的分析Comprehensive Evaluation of the High-quality Development of Regional Economy in Anhui Province:Analysis Based on the Entropy Weight TOPSIS Method朱晨ZHU Chen;武云亮WU Yun-liang(安徽财经大学国际经济贸易学院,蚌埠233030)(Institute of Finance and Trade Economics,Anhui University of Finance&Economics,Bengbu233030,China)摘要:以安徽省16个市为研究对象,以五大发展理念构建经济高质量发展综合评价体系,利用熵权改进的TOPSIS法分析比较2012-2018年安徽省经济发展水平的变化,通过Moran's I指数法对安徽省经济高质量发展进行了空间相关性检验。
结果表明:安徽省各地区经济高质量发展水平差距较大,整体经济高质量发展有着上升的趋势,经济高质量发展水平较高的皖中地区在绿色生态建设方面仍有较大潜力;各地区的经济发展水平呈现出逐渐减弱的正向集聚。
Abstract:Taking16cities in Anhui Province as the research object,the comprehensive evaluation system of high-quality economic-development is constructed with five development concepts.The paper analyzes and compares the changes of Anhui province's economic-development level from2012to2018by using TOPSIS method of entropy weight improvement.The spatial correlation test of high-quality economic development in Anhui Province is carried out by moran's I index method.The results show that the gap between the high-quality development level of economy in Anhui Province is large,the overall economic high-quality development is rising,and the middle Anhui area with high economic quality still has great potential in green ecological construction;the economic development level of each region is gradually weakening and positive agglomeration.关键词:经济高质量发展;熵权TOPSIS法;综合评价体系;空间相关性检验Key words:high-quality economic development;entropy TOPSIS method;comprehensive evaluation system;spatial correlation test 中图分类号:F127文献标识码:A文章编号:1006-4311(2021)10-0001-050引言我国经济已由高速增长阶段转向高质量发展阶段,长久以来,我们只关注了经济的高速发展,而忽略了经济高质量发展的必要性,由于我国经济呈现不平衡不充分发展,特别是区域经济表现出明显的差异,因而经济如何平衡有效的高质量发展是我国如今面临的首要问题。
审稿意见:统计审查
该论文在研究方法上主要采用了统计分析,这是研究的重要环节。
然而,从我审阅的资料和论文内容来看,作者在统计方面存在一些问题和不足,需要进行进一步的修改和完善。
首先,作者在描述统计方法时过于简单,没有详细说明所采用的具体统计方法和软件。
这使得读者无法理解分析的具体过程和细节,从而难以评估分析结果的可靠性和准确性。
为了解决这个问题,作者需要在描述统计方法时更加详细,包括所使用的具体统计方法、软件名称和版本号等。
其次,作者在分析数据时可能存在一些偏差。
例如,作者在描述样本分布时,可能存在一些主观性的判断和遗漏。
此外,作者在解释统计结果时也可能存在一些偏见或过于主观的推断。
为了避免这些问题,作者需要对数据进行更加客观和准确的分析,并且尽可能避免主观性的推断和偏见。
最后,作者需要更加注重统计学的严谨性和科学性。
在统计分析中,选择合适的统计方法和模型非常重要。
作者需要更加深入地了解各种统计方法和模型的特点和适用范围,并选择适合自己研究问题的统计方法和模型。
同时,作者还需要注意统计学的假设和限制条件,避免因为违反假设或超出适用范围而导致分析结果的偏差或误导。
综上所述,该论文在统计方面存在一些问题和不足,需要进行进一步的修改和完善。
作者需要更加注重统计学的严谨性和科学性,选择合适的统计方法和模型,并客观准确地分析数据和解释结果。
希望作者能够认真对待这些建议,对论文进行修改和完善,从而提高论文的质量和可靠性。
SPSS MIDTERMLecture11. Context (上下文,来龙去脉), contextual variable(脉络变数,语境变量)o Multilevel modeling attempts to separate the effects of personal characteristics and place characteristics (contextual effects) on behavioro In its most basic definition, a contextual variable is a variable that is constant within a group, but which varies by context. (在组内连续,组间差异较大)o Each of the nesting structures above has been used to address contextual effects: ->Students within a school - school resources effect on educational outcomes; Individuals within a neighborhood - effect of neighborhood dynamics on criminal activity; Workers within a labor market - the effect of racial composition on racial wage inequality; Firms within an industry - industrial context on organizational form?Children within a household - household health effects on child mortality.2. Multilevel other names, definitions3. System of Equations (multiple equations) Model vs. Mixed-Effect (single equation) model: Need to convert one to another4. Random effects: random intercepts vs. random slopes5. from empty to full effects6. Multilevel modeling assumptions->Level residuals are normally distributed->Residuals at the same level are uncorrelated with one another• Covariance = 0 for two different groups (协方差)• Covariance = 0 for two different individuals in the same or different groups->Residuals at different levels are uncorrelated with one another• Covariance = 0 for the same or different groups7. Comparison between multilevel and regressionMultilevel modeling is the statistical model that combines the individual level model representing disaggregate behavior with macro level model representing contextual variations in behavior.Comparison: Traditional regression modeling techniques are unable to partition the variation and just estimate a single term and refer to it as error. Multilevel modeling takes account the mean and the variability simultaneously is needed to uncover these relationships.Multilevel modeling canimprove estimation of individual effects. Can model cross-level effects. Can partition variance-covariance components8. Decomposition of total variations into level-1 (within) and level-2 (between)Total variance = within group variance (r) + between group variance (U intercept+U slop)The total variance is the sum of the squares of the departures of the observations around mean divided by the sample size.The variance of the individuals’ value around their group’s mean.Level 1, within school.The variance of the group means around overall mean. Level2, between schools.Lecture 21. Cross-classified structure: definitions, examples and comparisonsDefinition:lower level units belong to pairs or combinations of higher level units formed by crossing two or more higher level classifications with one another.It is a Non-Hierarchical structure. A level 1 individual can belong to different kinds of higher level groups.For example, a student A can live in region A and study in school A, a student B can also live in region A but study in school B, and student B can move and live in region C but still study in school B.Compared with hierarchical structures2. Multilevel modeling and clusteringProblem of clustering: people within a particular group or context tend to be more similar to each other in terms of an outcome variable than they are to people in a different group or context.3. Issues of group level analysis, individual level analysis1.Cannot infer individual level relationships from group-level relationships2.Means on means analysis is meaningless3.Mean does not reflect within group relationship4.Assume independence of residuals, but may expect dependency between individuals in thesame groupModeling spatial behavior purely at the individual level is prone to the atomistic fallacy(微体谬误,还原谬误), missing the context in which individual behavior occurs. It works only on micro level. Assume independence of residuals, but may expect dependency between individuals in the same group.Modeling spatial behavior purely at the aggregate level is prone to the ecological fallacy (区位谬误,生态谬误)that the results might not apply to individual behavior. Cannot infer individual level relationships from group-level relationships. Means on means analysis is meaningless. Mean does not reflect within group relationship.4. Fixed and random effects example questionsRandom effects:If you are interested in drawing inferences about some larger populationof levels that are onlyrepresented by the specific levels included in the study. Group and persons are random effects if you are generalizing to other groups and members like those included in the studyFixed effects:If you are interested in drawing inferencesonlyabout the specific levels of the term that are included in the study. Condition is a fixed effect if you are interested only in the levels of condition that are included in the studyLecture 31. Intraclass correlations coefficient (ICC) definitions, calculationsDefinitions: Intraclass Correlations Coefficient tells us how much of the total variability in the outcome lies between groups. Estimates how strongly two members from the same group resemble each other.It used to evaluate whether or not the level-2 variation(between group variations) is ignorable. The existence of ICC violates the assumption of independence required for a traditional linear models approach.2. Cross-level interaction: Interaction effect between level-1 and level-2Characteristics of contexts or settings may contribute to individual outcomesWithin contexts or groups, relationships may vary depending on (conditional on) group characteristicsThis is called cross level interaction, and will result in different slop and different intercept in different groups.For example, the effect of teacher’s enthusiasm on student’s grade may differ in different school, and this variance may can be explained by a characteristic of school like its reputation. That is to say, a level 2 var iable school’s reputation and a level 1 variable teacher’s enthusiasm have some interaction.3. Graphical demonstration of random effects by interception4. Centering: group mean and grand meanCentering issues usually focus on how the level- 1 explanatory variables are treated in the modelIt is a transformation of the explanatory variables. It only affects the interpretation of the intercept and has no impact on slope.Group mean centering: subtract the group mean from each person’s value of the independent variable. Eliminates knowledge of differences between schools.Grand mean centering: subtract the overall mean from each person’s value of the independent variableLecture 41. Ecological1)An ecological fallacy (or ecological inference fallacy)[1] is a logical fallacy in theinterpretation of statistical data where inferences about the nature of individuals are deduced from inference for the group to which those individuals belong. Ecological fallacy sometimes refers to the fallacy of division which is not a statistical issue. The four common statistical ecological fallacies are: confusion between ecological correlations and individual correlations, confusion between group average and total average,从宏观到微观,从群体到个体,结论不可以直接引用。