{"product_id":"nonparametric-statistical-tests","title":"Nonparametric Statistical Tests","description":"\u003cp\u003e\u003cstrong\u003eNonparametric Statistical Tests: A Computational Approach\u003c\/strong\u003e 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.\u003c\/p\u003e\u003cp\u003eThe book covers:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eNonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler test\u003c\/li\u003e\n\u003cli\u003ePermutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variability\u003c\/li\u003e\n\u003cli\u003eTests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data \u003c\/li\u003e\n\u003cli\u003eWell-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. \u003c\/li\u003e\n\u003cli\u003eTests 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 groups\u003c\/li\u003e\n\u003cli\u003eThe concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests\u003c\/li\u003e\n\u003cli\u003eThe applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designs\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eAlthough 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. \u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":54235723792728,"sku":"9781138114104","price":91.99,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0278\/1295\/4195\/files\/9781138114104_6bfb7fd9-ad3c-4258-9e34-10b1c49d6a05.jpg?v=1769695222","url":"https:\/\/agendabookshop.com\/products\/nonparametric-statistical-tests","provider":"Agenda Bookshop","version":"1.0","type":"link"}