Interpreting statistical tests for training interventions
The implementation of contemporary methods of statistical analysis is becoming increasingly popular within the sport science literature. Understanding and interpreting the results of these analyses is central to evidence-based practice. The outcomes generated by different statistical methods can result in distinctly different interpretations, and so understanding these is important in evaluating the efficacy of training techniques and interventions. As such, the primary aim of this article is to bridge the gap between academic statistical terminology and real world application, providing coaches with the effective tools to critically evaluate empirical literature by understanding the strengths and limitations of different types of statistical analyses used within training studies. The article will contrast traditional null-hypothesis significance testing with contemporary hypothesis testing (eg, parameter estimation), as well as evaluating possible future approaches to hypothesis testing (ie, Bayesian). The secondary aim of this article is to recommend the use of population inferences from the different statistical tests used within the training literature, and to consider the application of alternative forms of analysis where appropriate. Understanding these concepts will enable a coach to apply the correct interpretation of the different statistical outcomes to their own coaching practice.
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