LEADER 03614nam 22006495 450 001 9910299963803321 005 20200703230053.0 010 $a3-319-02744-1 024 7 $a10.1007/978-3-319-02744-9 035 $a(CKB)2560000000148956 035 $a(EBL)1697724 035 $a(OCoLC)881165939 035 $a(SSID)ssj0001204831 035 $a(PQKBManifestationID)11687278 035 $a(PQKBTitleCode)TC0001204831 035 $a(PQKBWorkID)11180536 035 $a(PQKB)10155338 035 $a(MiAaPQ)EBC1697724 035 $a(DE-He213)978-3-319-02744-9 035 $a(PPN)178316342 035 $a(EXLCZ)992560000000148956 100 $a20140411d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA Chronicle of Permutation Statistical Methods $e1920?2000, and Beyond /$fby Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (535 p.) 300 $aDescription based upon print version of record. 311 $a3-319-02743-3 320 $aIncludes bibliographical references and indexes. 327 $aPreface -- 1.Introduction -- 2.1920?1939 -- 3.1940?1959 -- 4.1960?1979 -- 5.1980?2000 -- 6.Beyond 2000 -- Epilogue -- References -- Acronyms -- Name Index -- Subject Index. 330 $aThe focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels. 606 $aStatistics 606 $aMathematics 606 $aHistory 606 $aStatistics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/S0000X 606 $aHistory of Mathematical Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/M23009 615 0$aStatistics. 615 0$aMathematics. 615 0$aHistory. 615 14$aStatistics, general. 615 24$aHistory of Mathematical Sciences. 676 $a510.9 676 $a519.5 676 $a519.5/4 676 $a519.54 700 $aBerry$b Kenneth J$4aut$4http://id.loc.gov/vocabulary/relators/aut$0148872 702 $aJohnston$b Janis E$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMielke Jr$b Paul W$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299963803321 996 $aA Chronicle of Permutation Statistical Methods$92540397 997 $aUNINA