Parametric procedures such as the t-test, ANOVA, Pearson's r, and ordinary least squares regression anchor most quantitative work submitted at the postgraduate level in psychology, yet the normality assumption on which they rest is routinely invoked without serious examination. This commentary identifies five recurring problems in dissertation practice: skipping assumption checks outright, reading skewness and kurtosis thresholds in isolation, treating Shapiro–Wilk output as a verdict, analysing single-item Likert responses as interval data, and using large sample size as blanket justification for ignoring distributional fit. These habits are placed against the institutional pressures that sustain them, and recommendations follow at programme, supervisor, and student level. Two supplementary files accompany the paper: a student decision checklist and a supervisor's evaluation guide. The argument throughout is that assumption checking belongs inside the analysis rather than alongside it.
Pooja Tyagi (Thu,) studied this question.