// Learn

A/B testing, learned by playing.

You cannot run a test you can defend if you do not understand what the numbers mean. But you do not need to memorize formulas either. Every lesson here gives you plain words, a thing you can poke, and the tool that does it for real. Start with lesson one and watch a test lie to you with your own eyes.

The path · from zero
01
Why one test can lie to you Interactive
Run two identical variants and watch one "win" by pure luck. The single idea that explains why every other lesson exists.
Start →
02
Conversion, lift, and what actually counts Next
Conversion rate, absolute vs relative lift, and why "the metric" is a decision you make before the test, not after.
03
Noise and significance (what a p-value really is)
The honest, jargon-free version of the number everyone quotes and almost nobody can define.
04
Power and sample size
Why a weak test can miss a real winner, and how to work out how much traffic you actually need.
05
The winner's curse
Why the wins that squeak past the bar are almost always smaller than they first look.
06
Peeking, and why it manufactures winners
Checking daily and stopping on a good day quietly turns a 5% error rate into roughly 1 in 4. See it happen.
07
Bayesian vs frequentist
Two languages for the same data. What each one actually tells you, and why the choice is not what saves a small store.
08
SRM: is your platform even honest?
Sample ratio mismatch, tracking loss, and the one check that tells you whether to trust any of the above.