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Published on: 2011-12-19
Released on: 2011-12-19
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Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading.The book covers:Nonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler testPermutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variabilityTests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data Well-known one-sample tests such as the sign test and Wilcoxon’s signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a one-sample bootstrap test are presented. Tests for more than two groups, the following tests are described in detail: the Kruskal-Wallis test, the permutation F test, the Jonckheere-Terpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groupsThe concepts of independence and correlation, and stratified tests such as the van Elteren test and combination testsThe applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designsAlthough the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap. Topics in Statistical Data Analysis: Revealing Facts from Data Introduction Developments in the field of statistical data analysis often parallel or follow advancements in other fields to which statistical methods are fruitfully ... SAS/STAT(R) 12.3 User's Guide Provides detailed reference material for using SAS/STAT software to perform statistical analyses including analysis of variance regression categorical data ... Statistics - Wikipedia Statistics is a branch of mathematics dealing with the collection analysis interpretation presentation and organization of data. In applying statistics to e.g ... Welcome to Statistica Sinica - Institute of Statistical ... STATISTICA SINICA is co-sponsored by Institute of Statistical Science Academia Sinica & International Chinese Statistical Association STATISTICS - University of Washington COLLEGE OF ARTS & SCIENCES STATISTICS Detailed course offerings (Time Schedule) are available for. Winter Quarter 2017; Spring Quarter 2017; Summer Quarter 2017 SAS/STAT(R) 9.2 User's Guide Second Edition Provides detailed reference material for using SAS/STAT software to perform statistical analyses including analysis of variance regression categorical data ... A biologist's guide to statistical thinking and analysis Abstract. The proper understanding and use of statistical tools are essential to the scientific enterprise. This is true both at the level of designing one's ... Statistical hypothesis testing - Wikipedia A statistical hypothesis is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables. A statistical hypothesis ... IBM SPSS Exact Tests - University of Sussex iii Copyright IBM Corporation. 1989 2012 Preface Exact Tests is a statistical package for analyzing continuous or categorical data by exact methods. Accepted Papers ICML New York City Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues Nihar Shah UC Berkeley Sivaraman Balakrishnan CMU Aditya Guntuboyina ...
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