Bayesian Statistics

Bayesian Statistics provides a comprehensive yet accessible introduction to Bayesian statistics, specifically tailored for any researcher with an interest in statistical methods. It covers the theoretical foundations of Bayesian inference, contrasting it with classical statistical methods like null hypothesis significance testing.

Thomas J. Faulkenberry, PhD, is a professor of psychological sciences and associate dean of the College of Graduate Studies at Tarleton State University in Stephenville, TX (USA). A mathematician by training, he teaches courses on statistics and mathematical modeling in the behavioral sciences, and his primary research areas are mathematical cognition and Bayesian statistics.

Preface 1. Review of basic concepts 2. The language of Bayesian statistics 3. Bayesian correlation 4. The Bayesian t-test 5. Bayesian analysis of variance 6. Bayesian linear regression 7. Next steps and further reading Glossary Answers to selected end-of-chapter exercises References