A single p-value is not a decision. Here are the three numbers — p-value, lift, confidence interval — that turn a dashboard spike into a verdict you can defend, plus how Bonferroni and sequential-testing corrections keep multiple A/B tests honest.
Adjusted R-squared is the correction that penalizes each new variable for not pulling its weight. Use it to compare nested models instead of chasing raw R².
Five numbers matter more than R-squared — and in this order. Why held-out validation, residual plots, and prediction intervals beat the headline score every time, and a practical workflow for shipping models that survive production.
An interactive visual proof that the distribution of sample means converges to a Normal bell curve regardless of source distribution, plus four controls and four source distributions you can dial in.
Why the straight line on the screen is wrong, the haversine formula is right, and the unit toggle decides who can read the answer. Three-coordinate anchor for great-circle distance on a sphere.