Drop Size Distributions for Irrigation Spray Nozzles

2024届上海市嘉定区高三上学期一模英语试题学校:___________姓名：___________班级：___________考号：___________一、语法填空Directions: After reading the passage below, fill in the blanks to make the passages coherent and grammatically correct. For the blanks with a given word, fill in each blank with the proper form of the given word;for the other blanks, use one word that best fits each blankSeeing Math on the PageMath and literature are probably two of the subjects that bring students headaches. However, scientists wonder 1 the beauty of math can be found in literary works. Once Upon a Prime: The Wondrous Connections between Mathematics and Literature, a book published recently by UK mathematician Sarah Hart, 2 (present) some interesting thoughts about "three". She argues that the beauty of this number is indeed evident in many works of western literature and languages in general.‘Three’ is the minimum number 3 a two-dimensional shape can be defined. For example, three sticks can create a triangle, a stable structure. Many common phrases are in three words, such as “ready, set, go”. Being the first things kids may learn, some nursery rhymes have a word 4 (repeat) three times, such as “row, row, row your boat”. In stories, there are usually three main characters, such as Harry, Ron and Hermione in the Harry Potter series. For a series of novels, there are usually three books 5 four, according to Hart.Why is it always the third son who behaves differently from his two older brothers, thus 6 (win) the princess? “The reason for this,” Hart explains, “ is obvious. We require two repetitions to get to know the pattern, 7 the breaking of the pattern in the third character can surprise or amuse us.”Similarly, another study by researchers at the University of Vermont also connected math and storytelling. They analyzed more than 1, 300 fiction books and arranged for 10, 000 words from the books 8 (rate) by 50 participants on a happiness scale of 1 to 9. Then the ratings 9 (categorize) into different graphs, which showed how the readers' emotions changed while reading. It turned out that each story fit perfectly into one of six basic graphs, a mathematical pattern.“The idea that one would 10 choose between mathematics and literatureis something of a tragedy, ”Hart says, “The two fields are fundamentally linked”.二、选词填空Directions: After reading the passage below, fill in each blank with a proper word given in theFarm of the Future in the Sky Five storeys off the ground at Colorado State University, a highly unlikely garden grows under a long row of rooftop solar panels. It's late November at 9 am, when the temperature is-2℃ and the wind is cutting. Not long before my arrival,cool-season foods like leafy greens still grow, 12 from the intense sunlight up there. This is no ordinary green roof, but an expansive and 13 outdoor laboratory. The idea behind it is explained by Jennifer Bousselot, the director of the rooftop farm. Solar panels tend to get too hot on conventional roof tops, and that heat reduces their efficiency while plants help cool them off. “If you have plants under there, ” Bousselot said, “they create ideal 14 for solar panels to operate. Also, the shade of the panels encourages the growth of plants. A win-win solution. ”Therefore, the overall goal of the rooftop farm is to grow more food for 15 urban populations while generating clean energy and making buildings more energy efficient. Without the sun beating down 16 on a bare roof, green roofs boost a building's energy efficiency by about 10 percent. That is, you don't need to run as much air-conditioning to 17 cool the place during a heat wave. This innovative approach can also maximize land use, making urban spaces not just consumers of resources, but also active18 to both energy and agricultural production.However, being 19 on a rooftop comes with more challenges than a typical farming site. The wind loads on a roof make it challenging to install a tracking system and irrigation (灌溉) is also trickier. The expenses are substantially increased due to higher20 costs and the difficulties of moving and installing all the sensors and materials high in the air.It is obviously early days for rooftop farms, but some effects were already evident. Instead of being big, dead spaces, roofs may act as booming ecosystems.三、完形填空“So …tell me about yourself. ”The toughest job interview question may seem like a softball from the interviewer’s perspective: It seems 21 because it feels like a free pass: no request for real-life examples, no technical challenge, not even the feared “What’s your biggest fault? ”Just…tell me anything.Receiving such an open invitation invites more 22 than opportunities, because you’re given no framework for your response —just a blank, clue-free paper. I often see this 23 situation in my point-making workshops: communicating without a point.What your prospective employer most needs from you is a point (“I am an important asset (资产) to the company”), not a 24 (“All about me”). But how do you get from the interviewer’s broad question to a specific and 25 point?Start with realizing that your interviewer already knows your job history thanks to your resume (简历). So you should be more than your 26 . Remember that interviews are more about making strong 27 than proving qualifications. This is a two-step process that will require some homework. First, identify what the organization specifically needs from this role. Second, 28 your response to position yourself as the best person to fill that need.Identifying the organization’s need means examining the job description like a treasure map. Phrases like “required, ”“must have, ”and “highly desired” mean what they say, so29 those in your planning. Items further down the list or labeled “preferred” may be less important, even if you meet those standards. The 30 of a job description can be telling as well. Descriptions that sound personal, or come right out and say “sense of humor preferred” indicate a workplace where people like to have fun. 31 , a very formal job posting might indicate a conservative workplace where people are expected to be serious about the work.Pulling from these soures, write down the three personal qualities they’re most looking for like “self-starter, ” “team player, ”or “interest in healthcare”. Now change the 32slightly to “I’m a self-starter” or “At work, my approach is ... ” Then pick a story from your professional life that 33 you filling that particular need of the job. Feel free to add details, but don’t 34 the primary elements. Assume they can smell a lie from a mile away, whether they can or can’t.In this way, you should do more than just widen eyes in the room. Why? Because you’ve matched who you are and your personal story with the company’s brand and primary need. You didn’t just tell them about you;you pointed out why you 35 to them. 21．A．hard B．easy C．huge D．small 22．A．missions B．joys C．comments D．risks 23．A．unlikely B．favourable.C．problematic D．competent 24．A．book report B．phone call C．desk lamp D．lunch break 25．A．declared B．tailored.C．rejected D．assessed 26．A．profile B．criterion C．dimension D．nickname 27．A．transitions B．judgments C．matches D．distributions 28．A．stabilize B．customize C．memorize D．authorize 29．A．diversify B．approve C．delete D．highlight 30．A．tone B．format C．picture D．length 31．A．For instance B．By contrast C．After all D．In addition 32．A．blogging B．networking C．messaging D．wording 33．A．illustrates B．suspends C．dismisses D．circulates 34．A．make up B．put off C．break down D．get through 35．A．submitted B．extended C．mattered D．shifted四、阅读选择To us, the kitchen was a mysterious place. Our kitchen at home was so simple: an old Sparks oven, a refrigerator, a sink, and a table. At the New Eastern, it was a busy factory. Almost an entire wall was taken up by a line of huge black woks (锅). This was my father’s stage. He strode (大步走) the length of the four woks, each one fired up by gas flames underneath. Beneath him, blocks of wood, raised off the ground an inch or two, served to give his legs and feet some spring.The sink was the size of a bathtub (浴); the refrigerator had glass doors and stretched threetimes as wide as the one at home. Every appliance was bigger, and there were things we never saw anywhere else, like the big metal oven in which my father hung long poles holding large pieces of pork. We could hear the fire roaring from the bottom of it. My dad would go about his business, and then, always at exactly the right time, he’d wander over, lift off the top, and take out several poles of barbecued pork—bright red, with black at the tips. If I happened by at that magical moment, I’d stop. “Yeet-gow!” I’d say. And he’d skillfully chop off a piece of the juicy, sweet meat. “One dollar!” he’d shout, and then hand it over.My father made the best food in town. There was nothing he wouldn’t try. He was once proud of a rock candy he invented and determined to sell at the front counter of the New Eastern. We, of course, served as his guinea pigs—we couldn’t bring ourselves to tell him the sad truth: The candy was so hard that it was uneatable. I rolled a piece around my mouth. “Tastes good, Ba-Ba, ”I said. Then, when he looked away, I spat it out.Sometimes, he liked to invent stories to us. Watching my little sister Shirley biting on an apple, he’d lean over. “Don’t eat the seed,” he said, “or an apple tree will grow inside you.” “What?” “Yes. Right inside your stomach, an apple tree!”36．It can be learned from paragraph 1 and 2 that____________.A．the author’s father can repair springs B．the author enjoys observing in thekitchenC．the author helps to cook difficult dishes D．the author’s family lives in a busyfactory37．How does the author develop the idea that “the kitchen is a mysterious place”?A．By describing how his father manages various tasks in the kitchen.B．By classifying the kitchen appliances into different categories.C．By contrasting the restaurant kitchen with the kitchen at home.D．By explaining why large pieces of pork were placed in the oven.38．The author mentions the incident of a rock candy in paragraph 3_____________.A．to highlight how he disliked the food his father madeB．to illustrate why they often kept secrets from his fatherC．to emphasize the troubled relationship with his fatherD．to show the family’s support for his father’s experiments39．Which of the following words can best describe the author’s father?A．dynamic and playful B．strict and innovativeC．talented and greedy D．hardworking and outdatedSocial engineering refers to the practice of using non-technical methods to trick people into doing something that gives away sensitive information. Here, watch this case ...40．It can be learned from “THE ATTACK” that_______.A．Sandra asks Marcus for his password.B．Marcus steals the key corporate data.C．The attacker gains Marcus's trust first.D．Sandra is a senior director of the bank. 41．Which of the following best fits the “?” in step ℃of “THE DEFENSE"?A．LESSON B．HEALTH C．PROGRAM D．FINANCE 42．Which of the following is covered in the case?A．What loss the company has suffered B．How Marcus regretted receiving the call C．What Natalie has found about the domain D．How effectively Ray responded to the attackNew research confirms that human footprints found in New Mexico are probably thescientists knew about human habitation and migration(迁徙).The footprints were discovered at the edge of an ancient lakebed in White Sands national park. According to the new paper published in the journal Science, they date back to between 21, 000 and 23, 000 years ago. Actually, the estimated age of the footprints was first reported in Science in 2021, but some researchers raised concerns about the dates. Questions focused on whether seeds of water plants used for the original dating may have absorbed ancient carbon from the lake—which could, in theory, throw off radiocarbon dating by thousands of years. But the new study presents two additional lines of evidence for the older date range. It uses two entirely different materials found at the site, ancient pollen(花粉)and stone grains.The reported age of the footprints challenges the once conventional wisdom that humans did not reach the Americas until a few thousand years before rising sea levels covered the Bering land bridge between Russia and Alaska, perhaps about 15, 000 years ago. “This is a subject that's always been controversial because it's so significant. It's about how we understand the last chapter of the peopling of the world, ”said Thomas Urban, an archaeologist (考古学家)at Comell University, who was involved in the 2021 study but not the new one.Thomas Stafford, an independent archaeological geologist in New Mexico, who was not involved in the study, said he“was a bit suspicious before”but now is convinced. The new study isolated about75, 000 grams of pure pollen from the same stone layer that contained the footprints. "Dating pollen is laborious but worthwhile, "said Kathleen Springer, a research geologist at the US Geological Survey and a co-author of the new paper.Ancient footprints of any kind can provide archaeologists with a quick look of a moment in time. While some archeological sites in the Americas point to similar date ranges—including necklaces carved from giant animal remains in Brazil—scientists still question whether such objects really indicate human presence. “White Sands is unique because there's no question these footprints were left by people, "said Jennifer Raff, a scientist at the University of Kansas, who was not involved in the study.43．The underlined word"upends”(paragraph 1)is closest in meaning to“_______".A．comprises B．connects C．challenges D．compares44．According to the passage, what is special about the new research?A．It shows the footprints were made by the Russians.B．It offers more convincing lines of evidence for dating.C．It confirms that the ancient humans enjoyed living by the lake.D．It reveals the footprints are much younger than previously thought.45．It can be inferred from the last paragraph that_____________.A．necklaces are valuable objects for archaeologists to date animalsB．human footprints are often sure signs of human presenceC．ancient objects in Brazil are excluded from the studyD．White Sands is one important archaeological site46．Which of the following might be the best title of the passage?A．Scientists Discovers New Species of Humans in AmericasB．Humans Reached Americas 15, 000 Years Earlier Than BelievedC．American Archaeologists Unearthed Valuable Manmade ObjectsD．New Research Confirms Early Human Presence in AmericasWhat to Know If Buying a Flipped HouseHouse flipping is hardly new. For someone who is working in the real estate market, a flipped or recently renovated (翻新的)home can be very appealing. But how about you, the home-hunter? 47You certainly don’t need to avoid flipped properties. A flipped property does have some strong selling points. A lot of its features and fixtures have been replaced or improved. Certainly, you’ll save on the time and trouble of doing the renovation yourself. But there are some things to watch out for if you’re considering buying one.48 For example, Alice recently toured a flipped house whose kitchen drawer was blocked by the refrigerator and the dishwasher wasn’t installed correctly -things that would prevent people from being able to function in there. Addressing issues like these can become costly, especially if you haven’t factored them into your budget.Don’t neglect your right to a professional inspection. 49 So getting an expert to go take a thorough look at the property is crucial, to make sure everything is up to code. It’s going to be really important to do your sewer(下水道)and separate roof inspections. Flipped houses may seem up-to-date on the surface, but shiny new finishes can sometimes masksubstandard work.Finally, flipped properties are rarely advertised as such. Therefore, it is crucial to work with aknowledgeable real estate agent. 50 When he tours a house that he suspects is being flipped, he’ll check who owned the home previously, and will reach out to other agents in his network to see if anyone has experience buying from them.A．The key is to look for places where improvements were done poorly.B．An experienced agent is probably going to have a better eye than the buyer.C．Is buying one of these quick-turnaround properties a good idea?D．Set aside money for any problems that may crop up or ask the seller to cover them. E．How do you know if the previous owner has moved out of the house?F．Flippers sometimes skip getting permits for the work they do.五、书面表达51．Directions: Read the following passage. Summarize the main idea and the main point(s)of the passage in no more than 60 words. Use your own words as far as possible.Dealing with One Missed WorkoutIt’s a common dilemma (图局)for anyone on a training plan: You miss one workout and become awashed with guilt. To make up for it, you add those extra miles to your next workout. But according to the professionals, this isn’t the right way to go about it. “A single workout is not going to make or break a training plan. The key to training is consistency over time,” says John Raglin, PhD, professor in the Department of Kinesiology at Indiana University Bloomington.When you miss a workout, the temptation is to think, “Oh, I’ve got to do more tomorrow”. But when you try to catch up on your workouts, you run a couple of risks: “Certainly an injury, but also becoming over-tired, which could ruin your training after that, ” says Raglin. This is a phenomenon called ‘non-functional overreaching’, “he says. Eventually, this could lead to overtraining syndrome (综合症), which is characterized by a decrease in performance later due to a long-term increase in training load without adequate recovery.So how do you move forward if you skipped a run or five?Well first, people download generalized training plans without understanding that they are meant to be adapted to life. There is a whole host of life stressors—job, kids, friendships, travel—and exercise is justanother type of stress. Actually, when things get chaotic in your life, it may be necessary to just let go. Next, if you missed a workout, you have to ask yourself why: “Was it just because your schedule got out of hand or because you were feeling overly exhausted? ” Understanding why you missed the workout can offer some insights into how to tailor your program to suit your lifestyle.___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ____________________六、翻译52．门后挂着毛巾和睡衣，方便客人使用。

a r X i v :c o n d -m a t /0404422v 2 [c o n d -m a t .s t a t -m e c h ] 24 A p r 2006GCEP-CFUM/2006/AC01Gap-Size Distribution Functions of a Random Sequential Adsorption Model ofSegments on the LineN.A.M.Ara´u jo and A.Cadilhe ∗GCEP-Centro de F ´isica da Universidade do Minho,4710-057Braga,Portugal(Dated:February 6,2008)We performed extensive simulations accompanied by a detailed study of a two-segment size ran-dom sequential model on the line.We followed the kinetics towards the jamming state,but we paid particular attention to the characterization of the jamming state structure.In particular,we stud-ied the effect of the size ratio on the mean-gap size,the gap-size dispersion,gap-size skewness,and gap-size kurtosis at the jamming state.We also analyzed the above quantities for the four possible segment-to-segment gap types.We ranged the values of the size ratio from one to twenty.In the limit of a size ratio of one,one recovers the classical car-parking problem.We observed that at low size ratios the jamming state is constituted by short streaks of small and large segments,while at high values of the size ratio the jamming state structure is formed by long streaks of small segments separated by a single large segment.This view of the jamming state structure as a function of the size ratio is supported by the various measured quantities.The present work can help provide insight,for example,on how to minimize the interparticle distance or minimize fluctuations around the mean particle-to-particle distance.PACS numbers:02.50.Ey,05.20.Dd,68.43.De,68.43.Mn,81.10.Dn,81.16Dn,81.16Nd,83.80Hj Keywords:I.INTRODUCTIONSince the 1939paper by Flory [1],for the deposi-tion of dimers on lattices,and the 1958paper by R´e nyi[2,3,4],for the deposition of segments on a line,the random sequential adsorption (RSA)model has become a paradigm for the study of many natural phenomena,not only in the traditional area of physical chemistry (re-action in polymer chains,chemisorption,colloids,etc),but also in the less traditional areas such as biology,ecology,and sociology [5,6,7,8,9,10].For instance,the use of RSA to determine the limiting coverage on surfaces requires an uniform deposition from stabilized,diluted suspensions of particles sized from 100˚A up to a micron by convective flow [10].Actual objects in-volve proteins and submicron colloidal particles [11].Re-cently,experimental interest has also included deposition on patterned surfaces,prepared by lithographic methods [12],and some theoretical work has been also performed [13,14].The basic dimer deposition model has suffered several extensions and generalizations,namely,coopera-tive sequential adsorption with adsorption rates depen-dent on the local environment [5],inclusion of relax-ational mechanisms such as detachment [15,16]and dif-fusion [17,18],and multi-layer deposition [19,20].Also,the RSA model and its extensions have been studied in one [21,22,23,24,25,26,27,28,29,30,31,32,33,34]and two dimensions [25,26,27,29,30,35,36,37]either in the continuum and lattice versions.More extended accounts can be found on recent reviews by Privman [6,7,9,10]and Evans[5].2 the simulations in Section II.In Section III,we presentour results and discuss them.Finally,we present ourconclusions in Section IV.II.THE MODEL AND THEORYWe consider the competitive deposition on the line ofsegments of two different sizes,namely short segments,which we denote as A-segments,and long ones,whichwe denote as B-segments,under the condition that theymust not overlap with each other upon adsorption,andtherefore,mimic an excluded volume,short-range inter-action.The fraction of the line occupied by the adsorbedsegments defines the coverage.We notice that it is possi-ble to re-scale,without loss of generality,the length scaleof the system so that A-segments are of unit length,whilethe size of B-segments is R.In this respect,one can re-gard the ratio of the length of B-segments relatively tothe length of A-segments as the size ratio,R=Length of a B-segmentα+β,(2)while that of a B-segment isp B=βTotal number of empty intervalsd x,(4)in the limit of d x being an infinitesimal quantity and thenumber of ensembles going to infinity.Thus,P∅(x)d x forthe jamming state has the property1P∅(x)d x=1.(5) Therefore,the jamming coverage is given by,θJ=1− 10xP∅(x)d x=1−<x>∅.(6) Discriminating all gaps between pairs of consecutively adsorbed segments by AA,AB,BA,and BB and defining density distribution functions P b(x),with b∈{AA,AB,BA,BB},one obtains the relation3P ∅(x )=P AA (x )+2P AB (x )+P BB (x ),(7)where we exploited the fact P AB (x )=P BA (x )for the present randomsequentialadsorption model.Notefromequations (5)and (7)that the P b (x )are not normalized.Keeping in mind the above definitions,it is now straight-forward to reckon higher moments of the gap-size distri-bution functions,defined by<x n>a =1x n P a (x )d xm !κa m .(10)where G a (k )is the so called characteristic function de-fined by [38]G a (k )=<eikx>a =1e ikx P a (x )d x1.000.74759580.0000671.050.75447530.0000621.100.75998290.0000631.200.76836520.0000581.250.77163580.0000631.300.77443770.0000541.400.77899460.0000631.500.78255200.0000641.600.78543490.0000531.750.78900160.0000662.000.79410380.0000582.100.79614140.0000532.250.79916610.0000582.500.80364440.0000602.750.80739960.0000653.000.81051720.0000663.250.81318500.0000603.500.81555900.0000653.750.81766750.0000734.000.81955000.0000704.500.82275400.0000635.000.82536670.0000675.500.82758480.0000746.000.82944810.0000767.000.83245370.0000768.000.83477290.00009410.000.83811120.00009712.000.84036950.0001014.000.84206030.0001116.000.84331870.0001318.000.84431860.0001220.000.84513770.00012S a =κa 3(κa 2)2,(17)respectively [38].4 III.RESULTS AND DISCUSSIONWe start by presenting our results with a study of thecoverage for the particular case of equalfluxes of incom-ing segments.In this respect,our study represents theparticular case of q=1/2of reference[34],but witha wider range of size ratios.In fact,results presented in[34]are valid for values of R<2.Our study also includesquantities,such as the dispersion,the fraction of emptyspaces,etc.,which are not possible to be computed bytheir method.In Fig.1(a),we show the time dependenceof the coverage,θ(t),for some of the values we simulated of the size ratio,R.However,we performed simulations for a wider range of values of the size ratio,namely for values of1,1.05,1.1,1.2,1.25,1.3,1.4,1.5,1.6,1.75,2, 2.1,2.25,2.5,2.75,3,3.25,3.5,3.75,4,4.5,5,5.5,6,7, 8,10,12,14,16,18,and20.Notice that our model for a size ratio of one boils down to deposition of segments of unit size on the line.The value of74.75958%±0.0067% for the jamming coverage is quite close to74.75979202%,first obtained by R´e nyi and subsequently calculated with larger precision by Blaisdell and Solomon[2,32,34].[39] The jamming coverage increases monotonically as a function of the size ratio,as shown in Fig.1(b)and Ta-ble I.This result is not entirely surprising,since for equal relativefluxes of incoming segments and for large,asymp-totic values of the size ratio,a stretch of the line is either fully covered by a large segment or paved by the small, unit size,segments with an upper limit of the coverage given by the above R´e nyi value.As both segment sizes can attempt deposition with equal probability,we get 1/2(1+0.7476)≡87.38%.However,this upper limit is not attained as one increases the value of the size ratio: the limiting value of the coverage around84.5%,obtained for a size ratio of20,remains lower as one can observe in Fig.1(b).In order to better analyze the structure of the jam-ming state,we now proceed to characterize the fraction of empty space distributed in terms of the different pairs of segments as we vary the size ratio.In Fig.2(a),we plot the fraction of the substrate left empty at the jam-ming state as a function of the size ratio for each pair of consecutive segments,namely of type AA,AB,and BB.In Fig.2(b),we also present the corresponding nor-malized population of the gap types.Consequently,in the latter case,the sum of the contributions of the four gap types adds up to the unit for every value of the size ratio.We observe that the fraction of empty space due to the AA-gaps increases monotonically with the size ra-tio.This can be understood by considering the signifi-cant drop in the population of BB-gaps at the jamming state as the size ratio increases,since these gaps must be smaller than unit.The probability of having two consec-utive B-segments adsorbed on the line rapidly decreases with the size ratio.Not only does the adsorption of both large segments imply a clean substrate,for example by the absence of smaller segments previously adsorbed on the line,but also both large segments must adsorb at a-5.0-4.5-4.0-3.5-3.0-2.5-2.0-1.5-1.0-0.50 10 20 30 40 50 60 70 80 90 100log(JammingCoverage-Coverage)Time [MCS]1.01.12.04.010.00.720.750.780.810.840.874 8 12 16 20JammingCoverageSize Ratio(a)(b)FIG.1:Coverage dependence on the size ratio for equal de-positingfluxes of each segment size.a)Plot of the coverage up to100time units for various values of the size ratio,namely, 1,1.1,2,4,and10.b)Plot showing the jamming coverage dependence on the size ratio.distance smaller than unit to prevent an A-segment to fit in.The latter situation becomes less and less proba-ble as the size ratio increases,and,to reach the jamming state,the leftover empty space between these large seg-ments must befilled with segments of unit size,thus,con-tributing to a higher fraction of empty space associated with AA-gaps and,consequently,to a higher value of the coverage.The slower decrease of the AB-gap population and of the corresponding coverage indicates a jamming state constituted by alternating streaks of A-segments separated by a single B-segment.This argument is fur-ther substantiated by the strong decay of the fraction of empty space associated with the BB-gaps for increasing values of the size ratio.This is also corroborated by the smoother decay of both the fraction of empty space and of the population of the AB-gap type,due to the breakdown of the BB-gap type as the size ratio increases.Finally, it can be seen in Fig.2(b)that as the size ratio diverges, the relative population of AB-and BB-gap types as com-pared to the corresponding population of the AA-gaps becomes less and less relevant,therefore leaving,in this50.030.060.090.121 2 3 4 5F r a c t i o n o f E m p t y S p a c eSize Ratio(a)0.03 0.06 0.090.12 0.15 48 12 16 200.20.40.6 0.81 2 3 4 5P o p u l a t i o nSize Ratio0.20.4 0.60.8 48 12 16 20(b)FIG.2:In both plots,one has the AA -,AB -,and BB -gap types represented by circles,squares,and triangles,respec-tively.a)Fraction of available empty space,at the jamming state.b)Normalized population of gaps at the jamming state.In the insets the size ratio varies between 1and 20.Please,refer to the text for further details.limit,long streaks of A -segments.In Fig.3(a),we show the distribution functions,P ∅(x ),P AA (x ),P AB (x ),and P BB (x ),at the jamming state,for a size ratio of one.Of course,at this size ratio (R =1),all gap types are equal as there is a single segment size.Therefore,one expects,as shown in Fig.3(a),to observe the collapse of the P AA (x ),P AB (x ),and P BB (x ),onto a single curve.The P ∅(x )distribution function also satisfies the relation P ∅(x )/4=P AA (x )=P AB (x )=P BB (x )in agreement with equation (7)for a size ratio of one.In the case of part b)of the same figure,we merely changed the value of the size ratio to 2.0,thus breaking the symmetries between the various gap types.Once again,adding the various gap distribution functions,for every value of x,accordingly to equation (7),actually reproduces P ∅(x ).As compared to part a),the AA -gap type increases its dominance,as pointed out above,while the AB -gap slightly lowers its contribution.The BB -gap significantly drops its influence,because it becomes less probable to have consecutive deposition of B -segments 00.01 0.02 0.03 0.04 0.050 0.2 0.4 0.6 0.8G a p S i z e D i s t r i b u t i o nSize RatioTotal AA AB BB0.01 0.02 0.03 0.04 0.050 0.2 0.4 0.6 0.8G a p S i z e D i s t r i b u t i o nSize Ratio(a)(b)Total AA AB BBFIG.3:Gap-size distribution functions at the jamming state:a)For a size ratio of one,the solid curve represents P ∅(x ),while the remaining AA -,AB -,and BB -gap types are identi-cal,and therefore fall onto a single curve.b)For a size ratio of 2.0,one observes the splitting of the various gap types.Please,refer to the text for further details.with gap lengths smaller than unit.Now,we proceed to the analysis of quantities involv-ing cumulants up to the fourth order,more specifically,the mean distance,dispersion,skewness,and kurtosis,as defined in equations (12-17).For each of the latter quantities,we studied their dependence on the size ratio at the jamming coverage limit as shown in Fig.4.Both the AA -and AB -gap types have rich non-monotonic be-havior,for the mean gap size,dispersion,skewness and kurtosis.For example,the minimum values of the gap size for the AA -and AB -gaps are not coincidental,as the minimum of the AA-gap occurs at a slightly higher value of the size ratio.The behavior of the dispersion shows the presence of both a minimum and maximum values.However,the opposite happens for the maximum value:the value of the size ratio at which it occurs is slightly lower for the AA -gap type.The minimum value occurs at the same value of R for these two gap types,within the error bounds.The skewness shows a maximum occur-ring at the different R values,namely,1.34and 1.29for6-1.20-1.00-0.80-0.60-0.40-0.20 1 2 3 4 5K u r t o s i sSize Ratio(a)(b)(c)(d)0.2000.4000.6000.800S k e w n e s s0.2700.2750.2800.285D i s p e r s i o n0.3000.3500.4000.450A v e r a g e D i s t a n c e-1.2-0.8-0.410200.000.400.8010200.270.280.2910200.300.400.501020FIG.4:Plots involving cumulants up to the fourth orderof the gap-size distribution functions for each gap type as a function of the size ratio.We use the same legend as in Fig.2.a)Average distance between pairs of segments.b)Dispersion of the distance between pairs of segments.c)Skewness.d)Kurtosis.TABLE II:The table summarizes the estimated values of R ,where the first four cumulants take maximum and minimum values,all measured with an error of ±0.005.The correspond-ing values of the cumulants are also included.gap typesminimum maximumR Value R Value7snugfits.As R increases the number of BB-gaps de-creases,to form AA-and AB-gaps,therefore,increasing the probability of snugfit events.The probability that for large values of R BB-gaps form a snugfit also de-creases.Consequently,the importance of snugfits de-creases for large values of R in agreement with Fig.4, where one observes monotonic behavior of the various cumulants in this regime.However,the large number of these events for values of R<∼1.55accounts for such rich behavior of the cumulants up to the fourth order.For example,the existence of minimum values of the AA-and AB-gaps sizes can now be understood as events from late stage kinetics close to the jamming state.The same argument also applies to the minimum values of the dis-persion,since this events tend to lower the uncertainties of adsorbed segments.More suble,it is the presence of maximum values for the both the AA-and AB-gaps and a minimum of the BB-gaps for values of R<1.05.Since the difference in size of both segments is small,both seg-ment sizes compete until coverage values become close to the jamming state,thus leading to snugfit events of the BB-gap.This competition leads to lessen the uncer-tainty in the BB-gaps,but it increases the uncertainties of the AA-and AB-gap types.For values of R≥1.55, the significant drop in the population of BB-gaps can be understood of the early onset of a mean gap size smaller than R at low coverage values,which effectively blocks the adsorption of large segments.Consequently,one ex-pects aflatter distribution function of the BB-gap type with increasing values of the size ratio,i.e.,the net effect of increasing the size ratio is to diminish the asymme-try of the BB-gap distribution function.The monotonic behavior of the BB-gap for large size ratios(R>1.55) stems from the absence of a competing mechanism.Fi-nally,the non-monotonic behavior of the remaining gap types is due to snugfit events,which the latter tend to askew the corresponding gap-size distribution functions by favoring small gap sizes.The jamming state for large size ratios,follows,there-fore,the picture of alternating streaks of A-segments in-terfaced with a single B-segment for large values of the size ratio.The presence of such streaks of A-segments interfaced with a single B-segment,prevents the AB-gap population to decrease slower than that of the BB-gap one.The snugfits events also tend to favor small gap sizes,and this effect makes the distribution function less flat and more askewed,thus increasing the value of the kurtosis and skewness of both the AA-and AB-gaps. (Fig.4(c-d)and Fig.3)IV.CONCLUSIONWe analyzed in detail the jamming structure of a model of random sequential adsorption on the line with two-segment sizes depositing with equalfluxes.The struc-ture of the jamming state is determined by the popula-tion of the various gap types,namely,the AA-,AB-,and BB-gap types.For large values of the size ratio,i.e.,for size ratios greater than1.55,snugfits become less signifi-cant,and the average distance,dispersion,skewness,and kurtosis monotonically approach their asymptotic values. 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大学英语优秀作文写家乡地理位置的My Hometown: A Place of Natural Beauty and Vibrant CultureMy hometown is a small city located in the southern part of China, nestled among mountains and rivers. With a population of around 500,000 people, it is a place where nature and culture come together to create a unique and vibrant atmosphere.Geographically, my hometown is situated in a lush valley, surrounded by mountains on three sides. The Yangtze River flows through the city, providing a source of water for irrigation and a scenic backdrop for residents and visitors alike. The climate is subtropical, with hot and humid summers and mild winters, making it a pleasant place to live all year round.One of the most striking features of my hometown is its natural beauty. The mountains that surround the city are covered in lush green forests, dotted with temples and shrines that date back centuries. The rivers that flow through the valley are a hub of activity, with fishermen casting their nets and boats gliding gracefully down the waterways. In the spring, the cherry blossoms bloom in a riot of pink and white, creating a stunning display that draws visitors from far and wide.In addition to its natural beauty, my hometown is also a place of rich cultural heritage. The city has a long history, dating back over a thousand years, and is home to a number of ancient temples, pagodas, and other historical sites. The local cuisine is renowned for its delicate flavors and use of fresh, seasonal ingredients, reflecting the bounty of the land and the sea.Despite its small size, my hometown is a vibrant and bustling place, with a lively market, bustling streets, and a thriving arts and music scene. The people here are warm and friendly, always ready to welcome visitors with a smile and a helping hand. Whether you are exploring the ancient temples, hiking in the mountains, or simply enjoying a leisurely stroll along the river, my hometown has something to offer everyone.In conclusion, my hometown is a place of natural beauty and vibrant culture, where the mountains meet the river and history meets the present. It is a place that is close to my heart, and I am proud to call it my home. I hope that more people will have the opportunity to visit and experience the beauty and warmth of my hometown for themselves.。

统计学术语中英文对照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Angular transformation 角转换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 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 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 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-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 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 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Partial correlation 偏相关Partial regression 偏回归Partial sorting 偏排序Partials residuals 偏残差Pattern 模式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 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 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Tuning constant 细调常数Two sided test 双向检验Two-stage least squares 二阶最小平方Two-stage sampling 二阶段抽样Two-tailed test 双侧检验Two-way analysis of variance 双因素方差分析Two-way table 双向表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Unit 单元Unordered　categories 无序分类Upper limit 上限Upward rank 升秩Vague concept 模糊概念Validity 有效性VARCOMP (Variance component estimation) 方差元素估计Variability 变异性Variable 变量Variance 方差Variation 变异Varimax orthogonal rotation 方差最大正交旋转Volume of distribution 容积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Wilcoxon paired test 威斯康星配对法/配对符号秩和检验Wild point 野点/狂点Wild value 野值/狂值Winsorized mean 缩尾均值Withdraw 失访Youden's index 尤登指数Z test Z检验Zero correlation 零相关Z-transformation Z变换。