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dc.contributor.editorPeter Hessling, Jan
dc.date.accessioned2021-04-20T16:09:41Z
dc.date.available2021-04-20T16:09:41Z
dc.date.issued2020
dc.identifierONIX_20210420_9781789239980_2661
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/67302
dc.description.abstractStatistical 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.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statisticsen_US
dc.subject.otherProbability & statistics
dc.titleStatistical Methodologies
dc.typebook
oapen.identifier.doi10.5772/intechopen.77486
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9781789239980
oapen.relation.isbn9781789239973
oapen.relation.isbn9781838806880
oapen.imprintIntechOpen
oapen.pages158


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