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The Compendium of Statistical Tests is a comprehensive single-volume reference covering 259 statistical tests across 25 chapters. Designed for working practitioners, researchers, and educators, it brings together procedures that are typically scattered across textbooks, journal articles, and software documentation into a single, consistently structured reference.
Every test is presented in a standardized two-page format that includes the formal test statistic, assumptions, hypotheses and decision rule, a plain-English explanation free of notation, practical warnings and best-practice guidance, a complete worked example from raw data to conclusion, common pitfalls, and software references in Python, R, and SAS.
The coverage spans the full breadth of modern statistical practice: normality and goodness-of-fit testing, means and variance comparisons, proportions and rates, nonparametric and rank-based methods, correlation and association, categorical data analysis, linear regression diagnostics, generalized linear models, mixed models, multivariate analysis, time series diagnostics, stationarity and unit root testing, cointegration, volatility modeling, randomness and independence, survival analysis, spatial statistics, quality control, equivalence and non-inferiority testing, robust methods, permutation and randomization tests, outlier detection, and Bayesian hypothesis testing.
Each chapter is preceded by a Conceptual Primer - a self-contained introduction that builds the mathematical and conceptual foundation needed before engaging with the individual test entries. The primers serve both as refreshers for experienced practitioners and as accessible introductions for those encountering a domain for the first time.
The book is organized to support rapid navigation. Readers can locate a test directly by chapter, by classification code, or through the index. Related tests addressing the same analytical goal are grouped together to facilitate comparison across competing procedures.
This reference is intended for statisticians, data scientists, quantitative analysts, econometricians, clinical researchers, engineers, graduate and undergraduate students, academic researchers, and instructors who teach applied statistics or quantitative methods. It does not replace formal statistical training but serves as the desk-side reference that practitioners and students alike reach for when they need the right test, correctly applied.
Format: Hardcover, 8.5 × 11 inches, color interior, 772 pages. Publisher: Pannala Series, 2026.
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