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Frequentism, as a book category, covers the philosophy and practice of frequentist statistics, where probability is interpreted as the long-run frequency of events under repeated sampling. Books in this genre explain core tools such as hypothesis testing (Fisher; Neyman–Pearson), p-values, confidence intervals, error rates, statistical power, maximum likelihood estimation, and experimental design, along with practical workflows for study planning and data analysis. The category spans textbooks, handbooks, applications across the sciences, and historical/philosophical treatments that contrast frequentist and Bayesian perspectives. Readers can expect both rigorous methodology and real-world case studies emphasizing reproducibility, controlled error rates, and inference justified by sampling theory.

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