You don't need to be a mathematician — you need to know which test, why, and what the output means. Statistics taught the way clinicians think.
Types of data, distributions, and the descriptive statistics every thesis needs first.
A simple flowchart: paired vs unpaired, parametric vs non-parametric — choosing t-test, Mann-Whitney, chi-square or ANOVA correctly.
What p<0.05 actually means, what it doesn't, and why confidence intervals tell you more.
Power, effect size and doing your own sample size calculation — demystified with orthopaedic examples.
When to use them, how to read the output tables, and reporting them in your thesis.
Spotting statistical red flags in published studies — and avoiding them in your own.
Waitlist members get founding-member pricing and free study notes while the course is in production.