This editorial discusses the common practice of using normality tests as a preliminary step for choosing between parametric and non-parametric methods. The editorial argues that such pre-testing is theoretically unfounded and practically harmful, as parametric tests are robust to moderate deviations from normality, while reliance on normality tests can distort error rates and mislead researchers.