Hypothesis Testing and Model Selection in the Social Sciences (Methodology in the Social Sciences Series) by David L. Weakliem explores the major approaches to hypothesis testing and model selection, blending statistical theory with practical recommendations illustrated through real-world social science examples.

The book systematically compares classical (frequentist) and Bayesian approaches, detailing their applications, discussing ways to reconcile differences between them, and evaluating key controversies and criticisms. It also delves into the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the importance of prior knowledge in Bayesian estimation and hypothesis testing.

Two easily calculated alternatives to standard hypothesis tests—Akaike information criterion (AIC) and Bayesian information criterion (BIC)—are discussed in depth. The companion website (www.guilford.com/weakliem-materials) provides data and syntax files for the book’s examples.

Published on April 25, 2016, with an ISBN-10 of 1462525652 and ISBN-13 of 978-1462525652, this 202-page book offers a comprehensive guide for students and professionals in the social sciences.