bmbstats – Bootstrap Magnitude-Based Statistics for Sports Scientists

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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Author Info: Mladen Jovanovic

I am a physical preparation coach from Belgrade, Serbia, grew up in Pula, Croatia (which I consider my home town). I was involved in physical preparation of professional, amateur and recreational athletes of various ages in sports such as basketball, soccer, volleyball, martial arts and tennis. Read More »
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This topic contains 2 replies, has 2 voices, and was last updated by  Mladen Jovanovic 5 months, 2 weeks ago.

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  • 08/05/2021 at 10:52 #31814

    Hello. I would like to ask you if you plan to do also some course regarding this bmbstat? Would be helpfull. Thank you. Matus.

    12/05/2021 at 12:12 #32742

    Hi Matus,

    After an extensive book, I do not plan to create a course in the near future. For some basic R data-wrangling and visualization check the Athlete Monitoring Course.

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