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Topic: Resampling (statistics)

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Resampling Stats in MATLAB In the learning and teaching of statistics, resampling is valuable because it allows students to address the questions of statistical inference in a way where their intuition can be brought to bear, by designing and carrying out simple numerical experiments on the computer. In addition to showing how resampling can be used to answer the simple, standard statistical inference questions found in traditional introductory statistics textbooks, we show cases where traditional introductory methods do not apply but where resampling techniques are straightforward extensions of the simple cases. Although the simple computer skills needed to use resampling are by no means trivial, we think they are far, far less formidable than the analytical mathematics that has been the bane of generations of statistics students who learned inference in the traditional way. www.macalester.edu /~kaplan/Resampling/preface.html   (1282 words)

Links We are beginning to explore using resampling and bootstrapping techniques in statistics. Resampling Statistics in Matlab Resampling Statistics in Excel Circular statistics is a set of trigonometric solutions to the problem of computing mean and variability measures. www.indiana.edu /~palab/links.htm   (353 words)

StatHomePage The idea of resampling is actually quite an old one in statistics, dating to at least 1935, but the application of such techniques had to wait until faster computers came along. Notice that the resampling approach is not concerned with what the estimated distances (or differences in mean distance) were, nor is it even particularly concerned about population parameters. When we speaking of "resampling," we are talking about procedures for either drawing many samples from some (pseudo-)population (bootstrapping), or constructing many rearrangements of the obtained sample values (randomization). www.uvm.edu /~dhowell/StatPages/Resampling/Resampling.html   (2301 words)

philosophy.html To me, one of the major problems facing people who are interested in exploring resampling procedures is understanding (or even recognizing) the difference in philosophy between the traditional parametric tests and resampling statistics. Much as I like the resampling approach to statistical tests, and easy as it is to understand the calculations behind them, once you get beyond the calculations and try to understand the true differences, things can get really messy. By doing this, they give the impression that resampling statistics are just something you drag out when assumptions are violated. www.uvm.edu /~dhowell/StatPages/Resampling/philosophy.html   (1415 words)

Statistics.com Courses: Introduction To Resampling Methods The sessions are based on the author's text, "Resampling Methods" (Birkhauser, 3rd edition, 2005) and on lectures he has given at the 2000 Joint Statistical Meetings, 2000-01 Deming Conference, as an ASA Travelling Lecturer, and during a recent tour of Western Europe. Provide hands-on experience with your choice of the following statistics software: Resampling Stats, R, S-PLUS, or Stata. The goal of the course is to give participants the confidence and tools necessary for the practice of statistics in their own research and in interpreting the research of others. www.statistics.com /content/courses/resampling/index.html   (768 words)

Resampling Stats Resampling (drawing repeated samples from the given data, or population suggested by the data) is a proven cure. Resampling is now the method of choice for confidence limits, hypothesis tests, and other everyday inferential problems. For a century the inherent difficulty of formula-based inferential statistics has baffled scientists, induced errors in research, and caused million of students to hate the subject. www.resample.com   (107 words)

Resampling methods: concepts, applications, and justification. Yu, Chong Ho In a study where one group of students learned statistics through resampling and the other learned it in a conventional manner, the resampling group did much better in solving statistical problems than the conventional group (cited in Rudner and Shafer, 1992). Thus, the conclusion derived from resampling should be qualified to be an inference in the sense of counterfactual logic, which is deeply embedded in the Fisherian tradition. Lunneborg (2000) emphasized that resampling is a form of "realistic data analysis" (p.556) for he realized that the classical method of comparing observations to models may not be appropriate all the time. pareonline.net /getvn.asp?v=8&n=19   (6496 words)

Resampling Stats The resampling operation will be repeated thousands (or tens of thousands) of times, and each time the value of your statistic of interest will be recorded. Resampling Stats for Excel is an add-in for Excel that facilitates bootstrapping, permutation and simulation procedures with data in Excel. The basic procedure is simple: Select the data you want to resample, select "resample" or "shuffle" from the Resampling Stats menu, then specify an output range for the resampled data. www.resample.com /content/software/excel/index.shtml   (360 words)

Resampling Software for Analysis and Validation of Enumerative and Binomal Sampling Plans(WCRL) Resampling with replacement can be useful if data sets contain relatively few observations and/or the user wishes to test high levels of precision or low error rates. Strengths: The major benefit of a resampling approach is that the underlying spatial distribution of the insect population is defined by actual field data rather than a theoretical model. Resampling without replacement is more representative of how samples would be taken in a field. www.wcrl.ars.usda.gov /software/rvspman.html   (2322 words)

III-4PUZ.txt Simon, Julian L. and Peter C. Bruce, "Evaluations of Teaching Introductory Statistics via Resampling", xerox, 1995. In resampling estimation it is of the highest importance to work in a careful, step-by-step fashion - to write down the steps in the estimation, and then to do the experiments just as described in the steps. When taught the resampling way, the instructor's first task is to resassure the students that they need not fear. www.juliansimon.com /writings/Resampling_Statistics/Part_III/III-4PUZ.txt   (3289 words)

Resampling Statistics RESAMPLING STATS 5.0 lets you take advantage of the past decade's revolution in statistics using resampling for hypothesis testing, confidence intervals, assessing standard errors and more. RESAMPLING STATS offers an easy-to-use, powerful tool to conduct repeated simulations (including the bootstrap) with your data, calculate test statistics, and analyze and view the results. A tutorial introduction to statistical inference using resampling. www.exetersoftware.com /cat/resamp/resampling.html   (729 words)

Stat/Math - Resampling Stats: Overview Resampling Stats is not a general purpose statistical computing tool. Resampling Stats users can always turn to their colleagues who are familiar with the software for help. Resampling Stats performs in a consistent and straight-forward manner and there are are no known bugs. www.indiana.edu /~statmath/stat/resamp/overview.html   (415 words)

Resampling Statistics Dave is of the opinion that resampling statistics will replace the traditional nonparametric statistics, and perhaps the traditional parametric statistics, in time. edition, is a brief introduction to resampling statistics. Howell’s resampling software is provided on the CD that comes with the text, but you should download the latest program from his web site. core.ecu.edu /psyc/wuenschk/StatHelp/Resampling.htm   (1647 words)

Product Page Develops three resampling approaches to statistical inference, each suited to a particular study design: Bootstrap Population Inference (for studies in which cases are randomly sampled), Rerandomization Causal Inference (for studies in which cases are randomly assigned), and Subsample Descriptive Inference (for nonrandom studies). Range and Precision of Scores / Size of Population / Size of Sample/ Roughness of Population Distribution / Parameters and Statistics of Interests / Scarcity of Random Samples/ Resampling Inference In DATA ANALYSIS BY RESAMPLING, Clifford Lunneborg argues that modern computing power has rendered the model-driven and assumption-plagued data analyses of the past unnecessary, obsolete, and inappropriate. www.duxbury.com /cgi-brookscole/course_products_bc.pl?fid=M2&discipline_number=17&product_isbn_issn=0534221106   (923 words)

Wiley::Introduction to Statistics Through Resampling Methods and R/S-PLUS Introduction to Statistics Through Resampling Methods and R/S-PLUS(r) aspires to introduce statistical methodology to a wide audience, simply, intuitively, and efficiently, through resampling from data at hand and by way of the computer programs R and S-PLUS. Introduction to Statistics Through Resampling Methods and Microsoft Office Excel (Paperback) Wiley::Introduction to Statistics Through Resampling Methods and R/S-PLUS www.wiley.com /WileyCDA/WileyTitle/productCd-0471715751.html   (354 words)

CONK! Encyclopedia: Statistics Resampling: A Marriage of Computers and Statistics (ERIC Digests) Statistician Job Outlook - Analysis of wages and working environment for the occupation conk.com /search/encyclopedia.cgi?q=Statistics   (1491 words)

"Resampling: Everyday statistical tool" Furthermore, in contrast to the older conventional statistics, which is a painful and humiliating experience for most students at all levels, the published studies show that students enjoy resampling statistics. In ancient times, mathematics in general, and statistics in particular, developed from the needs of governments and rich men to count their armies and flocks, and to enumerate the taxpayers and their possessions. The first step in using probability and statistics is to translate the scientific question into a statistical question. www.statistics.com /content/teaching/chance.html   (1491 words)

Presentation of National Awards in Statistics to Prof Bose’s work in resampling provides a deep and powerful understanding of the subject from the applied as well as the theoretical point of view. Bose received the National Award in Statistics for the year 2002-03, for young statisticians category, instituted in honour of Prof. He is a fellow of the Institute of Mathematical Statistics (IMS), USA, which is one of the world’s leading international societies of statistics. mospi.nic.in /presentation_of_national_awards.htm   (1491 words)

UT Department of Statistics Graduate Courses Statistical computing, numerical methods for linear models and generalized linear models, nonlinear statistical methods, matrix computations and special matrices, essentials of Monte Carlo simulation, and resampling techniques. Prereq: 2 courses in statistics and consent of the statistics department director of graduate studies. Prereq: 4 courses in graduate-level statistics or consent of statistics department director of graduate studies. bus.utk.edu /stat/ms/gradcourses.html   (1173 words)

Multivariate Statistics: Contents Discrete optimisation of statistical sample sizes in simulation by using the hierarchical resampling method Estimation on the poverty line as a problem of multivariate statistics Dependence structure of a multivariate distribution characterised by the correlation matrix www.vsppub.com /books/mathe/cbk-MulSta.html   (147 words)

Statistics Commerical Software Vendors: Main > F The course introduces the basic concepts and methods of statistics via resampling methods. If you or your company has statistics software that you'd like listed at www.statistics.com, please fill out the form below. We will wait 10 days before processing your payment; if you have a functioning link to statistics.com's courses, your payment will not be processed. jobs.statistics.com /content/commsoft/index.php3?§ion=f   (147 words)

"Resampling: Everyday statistical tool" Furthermore, in contrast to the older conventional statistics, which is a painful and humiliating experience for most students at all levels, the published studies show that students enjoy resampling statistics. The resampling method enables people to obtain the benefits of statistics and probability theory without the shortcomings of conventional methods, because it is free of mathematical formulas and restrictive assumptions and is easy to understand and use, especially in conjunction with the computer language and program RESAMPLING STATS. Rather, resampling is an entirely different method, and one of its strengths is that it does not depend upon the assumption that the data resemble the "Normal" distribution. www.statistics.com /content/teaching/chance.html   (147 words)

BioMed Central Full text Stability of response characteristics of a Delphi panel: application of bootstrap data expansion Resampling (bootstrapping) of a random sample of an unknown population is considered to model the distribution of that population, where the vaguer the knowledge about the population distribution is, the more valuable the bootstrapping technique proves to be [33]. In this study, statistics for each bootstrap resample were saved in memory and later used for estimation of sampling variance, confidence intervals and assessment of bias for the raw data [30]. Henderson AR: The bootstrap: a technique for data-driven statistics. www.biomedcentral.com /1471-2288/5/37   (5969 words)

index Mathematical/Computational Biology, Mathematical Finance, Satellite Navigation, Reliability and Fault Tolerance, Probability and Statistics, Resampling Methods, Asymptotic Theory, Probabilistic Algorithms, Mathematical Modeling and Simulation, Operations Research, Management Science. Responsible for research and analysis in nonelectronic reliability, reliability of combined hardware/software systems, software reliability, mathematical and statistical consulting, and modeling of system reliability/maintainability. Curriculum Development: Designed graduate courses in Computation, Linear Statistical Analysis, Measure-Theoretic Probability, Time Series, Advanced Mathematical Statistics, Mathematical Finance (Options Pricing), Reliability Theory, Nonparametric Statistics, Asymptotic Methods in Satistics, Simulation, Kalman Filtering; Mathematics Clinics in Neural Networks, Genetic Algorithms, Genetic Programming, Adaptive Clustering, Combinatorial Optimization, Satellite Availability and Performance Modeling, Algorithmic Defect Classfiication. fac.cgu.edu /~angusj/vitae   (5969 words)

INRIA - INédit 43 Statistical tests, resampling techniques such as cross-validation or bootstrap-that are very much used in statistical learning-the Bayesian approach that leads to the construction of model selection criteria that compensate a model adjustment quality with a measure of its complexity, these are powerful statistical inference tools to accomplish such a difficult task. Statistics makes it possible not only to take into account the noise present in the data, but also the heterogeneity of the models studied and the atypical values that may occur. Statistics in the broader sense covers the whole spectrum of techniques used to study random phenomena. www.inria.fr /actualites/inedit/inedit43_intro.en.html   (503 words)

May 96 ESSE Notes "What Some Puzzling Problems Teach About the Theory of Simulation and the Use of Resampling", by Julian L. Simon, _American Statistician_, Nov. 1994 "Probability and Statistics With Resampling Stats and Mathematica," by Julian L. Simon and Peter C. Bruce, _The Mathematica Journal_, Vol. Simon, manuscript PUZZLES & PROBLEMS "Easy Resampling Answers to Mosteller's and Others' 'Challenging' Problems in Probability", by Julian L. Simon (manuscript in progress). These are just a few of the items about us and by us that are available: ARTICLES & PAPERS "Pick a Sample," by Ivars Peterson, _Science News_, July 27, 1991 "Resampling: A Tool for Everyday Statistical Work," by Julian L. Simon and Peter C. Bruce, _Chance_, Vol. www.usra.edu /esse/june96essenotes.html   (503 words)

p-Value Adjustments When a resampling (bootstrap or permutation) method is used with only one test, the adjusted p-value is the bootstrap or permutation p-value for that test, with no adjustment for multiplicity, as described by Westfall and Soper (1994). It is exact when all of the p-values are uniformly distributed and independent, and it is conservative when the test statistics satisfy the positive orthant dependence condition (Holland and Copenhaver 1987). More specifically, assuming the same ordering of p-values as discussed previously, the resampling-style stepdown adjusted p-value for test r is the probability that the minimum pseudo-p-value of tests r,... www.id.unizh.ch /software/unix/statmath/sas/sasdoc/stat/chap43/sect14.htm   (1143 words)

PopTools - software for analysis of ecological models It has been used for studies of population dynamics, financial modelling, calculation of bootstrap and resampling statistics, and can be used for preparing spreadsheet templates for teaching statistics. These make it possible to run Monte Carlo simulations, conduct randomisation tests (including the Mantel test) and calculate bootstrap statistics. Some facilities are available for function minimisation and parameter estimation using maximum likelihood techniques, and there are a number of auditing and other tools that the author finds useful in his everyday work.  www.cse.csiro.au /poptools   (1143 words)

Statistics.com Courses - Resampling: And Exact Statistical Methods Resampling is now the method of choice for hypothesis tests, confidence limits, and other applied everyday problems in statistics and probability. Resampling -- including the bootstrap, permutation, and other non-parametric tests -- has taken statisticians by storm worldwide in the past decade. Following the first publication of the general technique (and the bootstrap) in 1969 by Julian Simon and subsequent independent development by Bradley Efron, resampling has become state-of-the-art practice. www.statistics.com /content/courses/resamp.html   (560 words)

Weekly Calendar "Motivation as a determinant for success in mathematics" Thursday, March 5 1:00 STATISTICAL COMPUTING SEMINAR - Room 459 MSC Arthur Yeh, Applied Statistics and Operations Research, BGSU "Resampling methods in regression" Friday, March 6 No Colloquium this week. "Motivation as a determinant for success in mathematics" 2:30 ALGEBRA SEMINAR - Room 447 MSC Curt Bennett, Mathematics and Statistics, BGSU. Wednesday, March 4 11:30 MATHEMATICS EDUCATION SEMINAR - Room 447 MSC Ron Harris, Mathematics and Statistics, BGSU. www-math.bgsu.edu /oldcalendars/1998-03-02.html   (175 words)

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