LEADER 03977nam 2200637 450 001 9910798685303321 005 20230125195930.0 010 $a1-63157-446-9 035 $a(CKB)3710000000831061 035 $a(BEP)4648712 035 $a(OCoLC)957560387 035 $a(CaBNVSL)swl00406796 035 $a(Au-PeEL)EBL4648712 035 $a(CaPaEBR)ebr11249676 035 $a(CaONFJC)MIL949214 035 $a(OCoLC)957588810 035 $a(CaSebORM)9781631574467 035 $a(MiAaPQ)EBC4648712 035 $a(EXLCZ)993710000000831061 100 $a20160829d2016 fy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 12$aA primer on nonparametric analysis$hVolume I /$fShahdad Naghshpour 205 $aFirst edition. 210 1$aNew York, New York (222 East 46th Street, New York, NY 10017) :$cBusiness Expert Press,$d2016. 215 $a1 online resource (xxvii, 120 pages) 225 1 $aEconomics collection,$x2163-7628 300 $aIncludes index. 311 $a1-63157-445-0 327 $aSection I. One-sample tests -- 1. Goodness of fit tests -- 2. Randomness tests -- 3. One-sample location inference -- Section II. One-sample tests -- 4. Comparing two unrelated samples: the Mann-Whitney U test -- 5. Goodness of fit for two samples -- Index. 330 3 $aNonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. In social sciences, often, it is not possible to obtain measurements, which renders customary analysis impossible. For example, it is not possible to measure utility but is possible to rank preference, which is based on the unmeasurable utility. Nonparametric methods provide theoretically valid options for analysis, making the use of unscientific methods unnecessary. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. The only prerequisite for this book is high school level elementary algebra. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. The book is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities. It is recommended that everyone read the Introduction and Chapter 1 because determining whether data are random or normally distributed is essential in the selection of parametric versus nonparametric methods. 410 0$aEconomics collection.$x2163-7628 606 $aNonparametric statistics 610 $aNonparametric statistics 610 $amedian 610 $aorder statistics 610 $arank 610 $aone sample 610 $atwo samples 610 $aseveral samples 610 $amultiple comparison 610 $anormality 610 $askewness 615 0$aNonparametric statistics. 676 $a519.5 700 $aNaghshpour$b Shahdad.$0890738 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910798685303321 996 $aA primer on nonparametric analysis$93730749 997 $aUNINA