Correlation
What r measures, what it does not, and when it lies.
- 1 lesson
- 14 min
- 2 simulations
Reading coefficients, controlling for confounders, and checking whether a regression can be trusted.
This is the real simulation from the module. No account needed.
A suggestion, never a lock — you can start here.
Every lesson's title and summary is public. The lessons themselves open once you own the track.
Every lesson in Data Analytics: Statistics & Data VisualizationSlope, intercept and R² — and what R² does not tell you.
Why a coefficient changes when another variable is added — and when that change fixes the answer, and when it breaks it.
Residuals, heteroscedasticity and overly influential points — four checks that decide whether that tidy coefficient table can be trusted.
What r measures, what it does not, and when it lies.
How to invert a probability, and why a 99%-accurate test can be wrong nine times in ten.
Why sample means behave so predictably, what a p-value really means, and how much data you need.
Designing, running and reading product experiments — including the mistakes that make the results meaningless.