Measuring Statistical Evidence Using Relative Belief

This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory. The author also addresses fundamental statistical issues, including the meaning of probability, the role of subjectivity, the meaning of objectivity, and the role of infinity and continuity.

List of contents

Statistical Problems. Probability. Characterizing Statistical Evidence. Measuring Statistical Evidence Using Relative Belief. Choosing and Checking the Model and Prior. Conclusions. Appendix. Bibliography. Index.

About the author

Michael Evans is a professor in the Department of Statistics at the University of Toronto. His research focuses on statistical inference, particularly a theory of inference based on the concept of relative belief. He is an associate editor of Bayesian Analysis and a former president of the Statistical Society of Canada.

Product details

• Authors: Michael Evans, Michael (University of Toronto Evans
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 23.06.2015
• EAN: 9781482242799
• ISBN: 978-1-4822-4279-9
• No. of pages: 250
• Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Subjects: Humanities, art, music > Psychology > Basic principles; Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; SCIENCE / Life Sciences / General, MATHEMATICS / Probability & Statistics / General, PSYCHOLOGY / Research & Methodology, Life sciences: general issues, Psychological methodology, Probability & statistics, Probability and statistics