The complete medical statistics curriculum, organized into 8 modules and 88 lessons — from study design to meta-analysis. Each lesson links to an in-depth guide; topics still in progress are marked Coming Soon.
Click a module to expand its lessons. Published lessons open the full guide; Coming Soon cards are placeholders for guides not yet written.
The essential groundwork before running any statistical test — study design, data types, sample size, and common pitfalls.
Tests for comparing two or more groups — t-tests, ANOVA, and their non-parametric counterparts.
Analyzing counts and proportions — chi-square family tests, risk measures, and clinical impact statistics.
Measuring relationships between variables and building predictive models.
Evaluating how well a test distinguishes disease from health.
Building and validating measurement instruments — reliability, agreement, and consistency.
Analyzing time-to-event outcomes — from censored data to hazard models.
Combining evidence across studies — from literature search to pooled effect estimates.