This second article in the editorial series serves as a practical guide to applying statistics in experimental physiology and biochemistry research. We frame statistical analysis as a continuous process, beginning at the experimental design stage with sample size justification and statistical power calculation. The article provides a detailed strategy for handling outliers, combining both visual and formal methods for their detection and analysis. A clear algorithm for selecting parametric and non-parametric tests, based on data type and study design, is presented and supported by illustrative tables. Significant attention is paid to the correct interpretation and presentation of results, including the reporting of exact p-values, effect sizes, and confidence intervals. A dedicated section analyzes common errors and contentious issues (e.g., multiple comparisons, p-hacking, confusion between replication types) that undermine the reliability of conclusions. The overarching goal of this material is to provide authors with a comprehensive framework that enhances the methodological rigor, transparency, and reproducibility of their research at all stages—from initial design to final publication.
Zaitsev Av (2025) studied this question.