000755290 000__ 03627cam\a2200481Ii\4500
000755290 001__ 755290
000755290 005__ 20230306141841.0
000755290 006__ m\\\\\o\\d\\\\\\\\
000755290 007__ cr\cn\nnnunnun
000755290 008__ 160511s2016\\\\sz\a\\\\ob\\\\001\0\eng\d
000755290 019__ $$a949327270
000755290 020__ $$a9783319287706$$q(electronic book)
000755290 020__ $$a3319287702$$q(electronic book)
000755290 020__ $$z9783319287683
000755290 020__ $$z3319287680
000755290 0247_ $$a10.1007/978-3-319-28770-6$$2doi
000755290 035__ $$aSP(OCoLC)ocn949378547
000755290 035__ $$aSP(OCoLC)949378547$$z(OCoLC)949327270
000755290 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dN$T$$dEBLCP$$dYDXCP$$dIDEBK$$dOCLCF$$dAZU$$dCOO
000755290 049__ $$aISEA
000755290 050_4 $$aQA276
000755290 08204 $$a519.5$$223
000755290 1001_ $$aBerry, Kenneth J.,$$eauthor.
000755290 24510 $$aPermutation statistical methods$$h[electronic resource] :$$ban integrated approach /$$cKenneth J. Berry, Paul W. Mielke, Jr., Janis E. Johnston.
000755290 264_1 $$aCham :$$bSpringer,$$c2016.
000755290 300__ $$a1 online resource (xx, 622 pages) :$$billustrations
000755290 336__ $$atext$$btxt$$2rdacontent
000755290 337__ $$acomputer$$bc$$2rdamedia
000755290 338__ $$aonline resource$$bcr$$2rdacarrier
000755290 504__ $$aIncludes bibliographical references and indexes.
000755290 5050_ $$aPreface -- 1.Introduction -- 2.Completely Randomized Data -- 3.Randomized Designs: Interval Data -- 4.Regression Analysis of Interval Data -- 5.Randomized Designs: Ordinal Data, I -- 6.Randomized Designs: Ordinal Data, II -- 7.Randomized Designs: Nominal Data -- 8.Randomized Designs: Nominal Data -- 9.Randomized Block Designs: Interval Data -- 10.Randomized Block Designs: Ordinal Data -- 11.Randomized Block Designs: Nominal Data -- Epilogue -- References -- Author Index -- Subject Index.
000755290 506__ $$aAccess limited to authorized users.
000755290 520__ $$aThis research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size. Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research. This research monograph addresses a statistically-informed audience, and can also easily serve as a textbook in a graduate course in departments such as statistics, psychology, or biology. In particular, the audience for the book is teachers of statistics, practicing statisticians, applied statisticians, and quantitative graduate students in fields such as psychology, medical research, epidemiology, public health, and biology.
000755290 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 11, 2016).
000755290 650_0 $$aMathematical statistics.
000755290 650_0 $$aPermutations.
000755290 7001_ $$aMielke, Paul W.,$$eauthor.
000755290 7001_ $$aJohnston, Janis E.,$$d1957-$$eauthor.
000755290 77608 $$iPrint version:$$z3319287680$$z9783319287683$$w(OCoLC)932095980
000755290 852__ $$bebk
000755290 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-28770-6$$zOnline Access$$91397441.1
000755290 909CO $$ooai:library.usi.edu:755290$$pGLOBAL_SET
000755290 980__ $$aEBOOK
000755290 980__ $$aBIB
000755290 982__ $$aEbook
000755290 983__ $$aOnline
000755290 994__ $$a92$$bISE