This book investigates the shift in scientific research methodology from traditional null hypothesis significance testing toward the use of effect sizes, confidence intervals, and meta-analysis. Geoff Cumming, a professor emeritus at La Trobe University, provides a comprehensive framework for adopting these more robust statistical practices. By focusing on estimation rather than binary significance, the author argues for a more nuanced interpretation of experimental data. The text serves as a technical guide for researchers and students aiming to improve the reproducibility and precision of their empirical work.

Experts recognize this work as a foundational text for researchers transitioning away from p-value-centric reporting. Readers frequently note the academic density of the prose, which requires a solid grasp of basic statistical concepts to fully utilize the provided methodologies.