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The Significance Test Controversy Revisited

The Fiducial Bayesian Alternative

  • Book
  • © 2014

Overview

  • Prepares students and researchers for experimental results report
  • Gives a genuine understanding of statistical inference procedures
  • Provides a Bayesian framework for a new approach to experimental data analysis and interpretation
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)

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Table of contents (10 chapters)

Keywords

About this book

The purpose of this book is not only to revisit the “significance test controversy,”but also to provide a conceptually sounder alternative. As such, it presents a Bayesian framework for a new approach to analyzing and interpreting experimental data. It also prepares students and researchers for reporting on experimental results. Normative aspects: The main views of statistical tests are revisited and the philosophies of Fisher, Neyman-Pearson and Jeffrey are discussed in detail. Descriptive aspects: The misuses of Null Hypothesis Significance Tests are reconsidered in light of Jeffreys’ Bayesian conceptions concerning the role of statistical inference in experimental investigations. Prescriptive aspects: The current effect size and confidence interval reporting practices are presented and seriously questioned. Methodological aspects are carefully discussed and fiducial Bayesian methods are proposed as a more suitable alternative for reporting on experimental results. In closing, basic routine procedures regarding the means and their generalization to the most common ANOVA applications are presented and illustrated. All the calculations discussed can be easily carried out using the freeware LePAC package.  

Authors and Affiliations

  • ERIS, Laboratoire de Mathématiques Raphaël Salem, Université de Rouen UMR 6085 CNRS, St Et. du Rouvray CEDEX, France

    Bruno Lecoutre

  • ERIS, IJLRA UMR-7190 case 162, Université Pierre et Marie Curie CNRS, Paris Cedex 05, France

    Jacques Poitevineau

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