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Bayesian Statistics: An Introduction

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Unraveling statistics through Bayesian hypothesis probabilities.

If you're grappling with the concepts of hypothesis testing and want an in-depth yet accessible dive into Bayesian statistics, this book by Peter M Lee is a worthwhile read. It's perfect for anyone in advanced undergraduate or postgraduate studies who is curious about the differences between Bayesian and classical statistics, and seeks clarity on incorporating data into statistical reasoning. Lee's approachable explanations and new chapters on trending topics like Gibbs sampling make it a relevant and insightful resource.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
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Bayesian Statistics: An Introduction

Regular price $10.90 Now $6.90 Save 37%
Unit price
per
ISBN: 9780852643099
Authors: Peter M. Lee
Publisher: E. Arnold
Date of Publication: 1992-01-01
Format: Paperback
Related Collections: Philosophy, Personal Development, Science
Related Topics: Mathematics, Popular Science, Theory
Goodreads rating: 0.0
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Description

Statistics is concerned with investigating the degree of confidence we can have in various hypotheses. The Bayesian approach is distinguished by giving each hypothesis a probability and then modifying it in the light of the experimental data. This is controversial because for a new theory with no data available, an element of guesswork has to be involved. The author presents the ideas behind Bayesian statistics at a level suitable for advanced undergraduate or postgraduate students. The discrepancies between the conclusions of Bayesian and classical statistics are highlighted.
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Similar Reads

Unraveling statistics through Bayesian hypothesis probabilities.

If you're grappling with the concepts of hypothesis testing and want an in-depth yet accessible dive into Bayesian statistics, this book by Peter M Lee is a worthwhile read. It's perfect for anyone in advanced undergraduate or postgraduate studies who is curious about the differences between Bayesian and classical statistics, and seeks clarity on incorporating data into statistical reasoning. Lee's approachable explanations and new chapters on trending topics like Gibbs sampling make it a relevant and insightful resource.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.