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010   $a981-15-2537-4
024 7 $a10.1007/978-981-15-2537-7
035   $a(CKB)4100000011233854
035   $a(DE-He213)978-981-15-2537-7
035   $a(MiAaPQ)EBC6199816
035   $a(PPN)248393359
035   $a(EXLCZ)994100000011233854
100   $a20200514d2020      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aIllustrating Statistical Procedures: Finding Meaning in Quantitative Data $b[electronic resource] /$fby Ray W. Cooksey
205   $a3rd ed. 2020.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020.
215   $a1 online resource (XXV, 737 p. 228 illus., 75 illus. in color.) 
300   $aIncludes index.
311   $a981-15-2536-6 
327   $aIntroduction -- Chapter 1: The logic and language of statistical analysis Reference -- Chapter 2: Measurement issues in quantitative research -- Chapter 3: Computer programs for analysing quantitative data -- Chapter 4: Example research context aand quantitative data set -- Chapter 5: Descriptive statistics for summarising data -- Chapter 6: Correlational statistics for characterising relationships -- Chapter 7: Inferential statistics for hypothesis testing relationships -- Chapter 8: Other commonly-used statistical procedures relationships -- Chapter 9: Specialised statistical procedures -- Appendices -- Index.
330   $aThis book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
606   $aStatistics 
606   $aBig data
606   $aData mining
606   $aManagement information systems
606   $aDatabase management
606   $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001
606   $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aSoftware Management$3https://scigraph.springernature.com/ontologies/product-market-codes/522050
606   $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024
615  0$aStatistics .
615  0$aBig data.
615  0$aData mining.
615  0$aManagement information systems.
615  0$aDatabase management.
615 14$aStatistical Theory and Methods.
615 24$aBig Data/Analytics.
615 24$aData Mining and Knowledge Discovery.
615 24$aSoftware Management.
615 24$aDatabase Management.
676   $a780
700   $aCooksey$b Ray W$4aut$4http://id.loc.gov/vocabulary/relators/aut$01015113
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996418259803316
996   $aIllustrating Statistical Procedures: Finding Meaning in Quantitative Data$92368788
997   $aUNISA