
Bayesian Statistics the Fun Way
by Will Kurt (2019)
Like 'Introduction to Bayesian Statistics', this book makes Bayesian statistics accessible for learning.

by William M. Bolstad (2004)
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. In Bayesian statistics the rules of probability are used to make inferences about the parameter. Prior information about the parameter and sample information from the data are combined using Bayes theorem. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. This book uniquely covers the topics usually found in a typical introductory statistics book but from a Bayesian perspective.
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by Will Kurt (2019)
Like 'Introduction to Bayesian Statistics', this book makes Bayesian statistics accessible for learning.

by Aubrey Clayton (2021)
Similar to 'Introduction to Bayesian Statistics', this book explores the development and context of statistical ideas.

by Richard McElreath (2015)
Following 'Introduction to Bayesian Statistics', this offers a next logical step in practical Bayesian analysis.

by Osvaldo Martin, Ravin Kumar, Junpeng Lao (2018)
This book, like 'Introduction to Bayesian Statistics', teaches both Bayesian math and programming skills.

by Ben Lambert (2017)
Aimed at newcomers like 'Introduction to Bayesian Statistics', this guide builds Bayesian concepts gradually.
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