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008 160829s2016 nyu foa 001 0 eng d
020 _z9781631574450
_qpaperback
020 _a9781631574467
_q(electronic bk.)
035 _a(MiAaPQ)EBC4648712
035 _a(Au-PeEL)EBL4648712
035 _a(CaPaEBR)ebr11249676
035 _a(CaONFJC)MIL949214
035 _a(OCoLC)957588810
040 _aMiAaPQ
_beng
_erda
_epn
_cMiAaPQ
_dMiAaPQ
050 4 _aQA278.8
_b.N246 2016
082 0 _a519.5
_223
100 1 _aNaghshpour, Shahdad.,
_eauthor.
245 1 2 _aA primer on nonparametric analysis.
_nVolume I /
_cShahdad Naghshpour.
250 _aFirst edition.
264 1 _aNew York, New York (222 East 46th Street, New York, NY 10017) :
_bBusiness Expert Press,
_c2016.
300 _a1 online resource (xxvii, 120 pages)
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
490 1 _aEconomics collection,
_x2163-7628
500 _aIncludes index.
505 0 _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.
506 1 _aAccess restricted to authorized users and institutions.
520 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.
588 _aTitle from PDF title page (viewed on August 29, 2016).
590 _aElectronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
650 0 _aNonparametric statistics.
653 _aNonparametric statistics
653 _amedian
653 _aorder statistics
653 _arank
653 _aone sample
653 _atwo samples
653 _aseveral samples
653 _amultiple comparison
653 _anormality
653 _askewness
655 4 _aElectronic books.
776 0 8 _iPrint version:
_z9781631574450
797 2 _aProQuest (Firm)
830 0 _aEconomics collection.
_x2163-7628
856 4 0 _uhttps://ebookcentral.proquest.com/lib/bacm-ebooks/detail.action?docID=4648712
_zClick to View
999 _c263896
_d263895