Get personalized book recommendations based on your reading history and preferences. Our algorithm analyzes your favorite books and reading patterns to suggest your next great read.

“P-values” is a category for books that explore statistical significance and hypothesis testing—the ideas, practices, and debates behind how researchers judge evidence. It spans accessible introductions to probability and inference; methodological texts on computing, interpreting, and reporting p-values alongside confidence intervals, power, and effect sizes; field-specific guides for medicine, psychology, economics, and beyond; and critiques of common pitfalls such as p-hacking, multiple comparisons, and false discoveries tied to the replication crisis. Readers will also find histories of Fisher and the Neyman–Pearson framework, discussions of frequentist vs. Bayesian approaches, and practical handbooks on reproducible research, preregistration, and transparent analysis. Designed for students, researchers, and data-curious readers, this shelf clarifies what statistical evidence means, how it’s misused, and how to make more reliable decisions with data.

Filter books by their publication year. Enter the earliest year (Start) and latest year (End) to find books published within that period. Leave either field empty to search from the beginning of time or up to the present day.