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001482788 001__ 1482788
001482788 003__ OCoLC
001482788 005__ 20231128003351.0
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001482788 008__ 231102s2023\\\\sz\a\\\\ob\\\\001\0\eng\d
001482788 019__ $$a1406407513
001482788 020__ $$a9783031417139$$qelectronic book
001482788 020__ $$a3031417135$$qelectronic book
001482788 020__ $$z9783031417122
001482788 020__ $$z3031417127
001482788 0247_ $$a10.1007/978-3-031-41713-9$$2doi
001482788 035__ $$aSP(OCoLC)1407112136
001482788 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP
001482788 049__ $$aISEA
001482788 050_4 $$aQA276$$b.W55 2023
001482788 1001_ $$aWilcox, Rand R.,$$eauthor.
001482788 24512 $$aA guide to robust statistical methods /$$cRand R. Wilcox.
001482788 264_1 $$aCham :$$bSpringer,$$c2023.
001482788 300__ $$a1 online resource (xvii, 326 pages) :$$billustrations
001482788 336__ $$atext$$btxt$$2rdacontent
001482788 337__ $$acomputer$$bc$$2rdamedia
001482788 338__ $$aonline resource$$bcr$$2rdacarrier
001482788 504__ $$aIncludes bibliographical references and index.
001482788 5050_ $$a1. Introduction -- 2. The one-sample case -- 3. Comparing two independent groups -- 4. Comparing two dependent groups -- 5. Comparing multiple independent groups -- 6. Comparing multiple dependent groups -- 7. Robust regression estimators -- 8. Inferential methods based on robust regression estimators -- 9. Measures of association -- 10. Comparing groups when there is a covariate.
001482788 506__ $$aAccess limited to authorized users.
001482788 520__ $$aRobust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true -- but they continue to perform well in situations where classic methods perform poorly. This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data. The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
001482788 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 30, 2023).
001482788 650_0 $$aMathematical statistics.
001482788 655_0 $$aElectronic books.
001482788 77608 $$iPrint version: $$z3031417127$$z9783031417122$$w(OCoLC)1390187513
001482788 852__ $$bebk
001482788 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-41713-9$$zOnline Access$$91397441.1
001482788 909CO $$ooai:library.usi.edu:1482788$$pGLOBAL_SET
001482788 980__ $$aBIB
001482788 980__ $$aEBOOK
001482788 982__ $$aEbook
001482788 983__ $$aOnline
001482788 994__ $$a92$$bISE