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100   $a20230623d2020      uy             0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aStatistical Methodologies /$fedited by Jan Peter Hessling
210  1$aLondon :$cIntechOpen,$d2020.
215   $a1 online resource (158 pages)
311   $a1-83880-688-1 
330   $aStatistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence.
606   $aStatistics$xMethodology
615  0$aStatistics$xMethodology.
676   $a519.502855133
702   $aHessling$b Jan Peter
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910688592103321
996   $aStatistical Methodologies$92270978
997   $aUNINA