On the Foundations of Statistical Inference, I: Binary Experiments

Allan Birnbaum

ISBN 10: 1330258649 / ISBN 13: 9781330258644

Published by Forgotten Books, 2018

About this Item

Print on Demand. This book explores how statistical inference problems can be solved directly from the likelihood functions of binary experiments, providing interpretations of their numerical values in terms of probabilities of committing various types of errors. It establishes the likelihood function as the primary, sufficient basis for making inferences and presents a novel analysis of problems of informative inference, which are usually formulated in terms of hypothesis testing and decision making. The book argues that evidential interpretations of outcomes in terms of supporting or refuting specific statistical hypotheses are not only valid but necessary for understanding the role of statistical experiments in empirical research. By focusing on the likelihood function and its properties, the author provides a fresh perspective on the foundations of statistical inference that challenges the dominance of hypothesis testing in statistical practice. This book will be of interest to statisticians, philosophers of science, and anyone interested in the foundations of statistical inference, particularly as it relates to problems of informative inference. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.

Seller Inventory # 9781330258644_0

Bibliographic Details

• Title: On the Foundations of Statistical Inference, I: Binary Experiments
• Publisher: Forgotten Books
• Publication Date: 2018
• Language: English
• ISBN 10: 1330258649
• ISBN 13: 9781330258644
• Binding: Paperback
• Condition: New
• Book Type: print-on-demand item
• Seller catalogs:
  • Statistics

About this title

Synopsis

This book explores how statistical inference problems can be solved directly from the likelihood functions of binary experiments, providing interpretations of their numerical values in terms of probabilities of committing various types of errors. It establishes the likelihood function as the primary, sufficient basis for making inferences and presents a novel analysis of problems of informative inference, which are usually formulated in terms of hypothesis testing and decision making. The book argues that evidential interpretations of outcomes in terms of supporting or refuting specific statistical hypotheses are not only valid but necessary for understanding the role of statistical experiments in empirical research. By focusing on the likelihood function and its properties, the author provides a fresh perspective on the foundations of statistical inference that challenges the dominance of hypothesis testing in statistical practice. This book will be of interest to statisticians, philosophers of science, and anyone interested in the foundations of statistical inference, particularly as it relates to problems of informative inference.