bmbstats: Bootstrap Magnitude-Based Statistics for Sports Scientists

The aim of this book is to provide an overview of the three classes of tasks in statistical modeling: description, prediction, and causal inference. Statistical inference is often required for all three tasks. A short introduction to frequentist null-hypothesis testing, Bayesian estimation, and bootstrap are provided. Special attention is given to the practical significance with the introduction of magnitude-based estimators and statistical inference by using the concept of the smallest effect size of interest (SESOI). Measurement error is discussed with the particular aim of interpreting individual change scores. In the second part of this book, common sports science problems are introduced and analyzed with the bmbstats package.

This book is FREE open-source and published under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, while the bmbstats R package is open-source and published under MIT license.

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