Statistical Methodologies

Jan Peter Hessling

ISBN 10: 1789239974 / ISBN 13: 9781789239973

Published by Intechopen Feb 2020, 2020

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical 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. 158 pp. Englisch.

Seller Inventory # 9781789239973

Bibliographic Details

• Title: Statistical Methodologies
• Publisher: Intechopen Feb 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 1789239974
• ISBN 13: 9781789239973
• Binding: Buch
• Condition: Neu
• Dimensions: 266W x 185H x 16D millimeters 266 millimeters width by 185 millimeters height by 16 millimeters depth
• Weight: 562 grams

About this title

Synopsis

Statistical 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.