{"product_id":"nonparametric-statistical-methods-using-r-hardcover","title":"Nonparametric Statistical Methods Using R - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJohn Kloke\u003c\/b\u003e (Author), \u003cb\u003eJoseph McKean\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003ePraise for the first edition: \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\"This book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R.\"\u003cbr\u003e-The American Statistician\u003c\/p\u003e\u003cp\u003eThis thoroughly updated and expanded second edition of \u003cb\u003eNonparametric Statistical Methods Using R\u003c\/b\u003e covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded to include discussions on ties as well as power and sample size determination. Common machine learning topics --- including k-nearest neighbors and trees --- have also been included in this new edition.\u003c\/p\u003e\u003cp\u003eKey Features: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eCovers a wide range of models including location, linear regression, ANOVA-type, mixed models for cluster correlated data, nonlinear, and GEE-type.\u003c\/li\u003e \u003cli\u003eIncludes robust methods for linear model analyses, big data, time-to-event analyses, timeseries, and multivariate.\u003c\/li\u003e \u003cli\u003eNumerous examples illustrate the methods and their computation.\u003c\/li\u003e \u003cli\u003eR packages are available for computation and datasets.\u003c\/li\u003e \u003cli\u003eContains two completely new chapters on big data and multivariate analysis.\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eThe book is suitable for advanced undergraduate and graduate students in statistics and data science, and students of other majors with a solid background in statistical methods including regression and ANOVA. It will also be of use to researchers working with nonparametric and rank-based methods in practice.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eJohn D. Kloke\u003c\/b\u003e is a bit of a jack-of-all-trades as he has worked as a clinical trial statistician supporting industry as well as academic studies and he also served as a teacher-scholar at several academic institutions. He has held faculty positions at the University of California - Santa Barbara, University of Wisconsin - Madison, University of Pittsburgh, Bucknell University, and Pomona College. An early adopter of R, he is an author and maintainer of numerous R packages, including Rfit and npsm. He has published papers on nonparametric rank-based estimation, including analysis of cluster correlated data.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eJoseph W. McKean\u003c\/b\u003e is a professor emeritus of statistics at Western Michigan University. He has published many papers on nonparametric and robust statistical procedures and has co-authored several books, including Robust Nonparametric Statistical Methods and Introduction to Mathematical Statistics. He co-edited the book Robust Rank-Based and Nonparametric Methods. He served as an associate editor of several statistics journals and is a fellow of the American Statistical Association.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 480\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 20, 2024\u003c\/div\u003e\n            ","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":50340038541549,"sku":"9780367651350","price":158.74,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0020\/8918\/9441\/files\/f_-MDd0SKh9780367651350.webp?v=1785119668","url":"https:\/\/www.webster.direct\/en-ca\/products\/nonparametric-statistical-methods-using-r-hardcover","provider":"Webster.Direct","version":"1.0","type":"link"}