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010   $a3-319-28770-2
024 7 $a10.1007/978-3-319-28770-6
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035   $a(DE-He213)978-3-319-28770-6
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100   $a20160503d2016      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aPermutation Statistical Methods $eAn Integrated Approach /$fby Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (XX, 622 p. 180 illus.)
311 08$a3-319-28768-0 
320   $aIncludes bibliographical references and indexes.
327   $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.
330   $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.
606   $aStatistics
606   $aBiometry
606   $aScience$xHistory
606   $aStatistical Theory and Methods
606   $aBiostatistics
606   $aHistory of Science
615  0$aStatistics.
615  0$aBiometry.
615  0$aScience$xHistory.
615 14$aStatistical Theory and Methods.
615 24$aBiostatistics.
615 24$aHistory of Science.
676   $a519.5
700   $aBerry$b Kenneth J.$4aut$4http://id.loc.gov/vocabulary/relators/aut$0148872
702   $aMielke Jr$b Paul W$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aJohnston$b Janis E$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254062103321
996   $aPermutation Statistical Methods$92124854
997   $aUNINA