3 min read
Statistical significance explained without any maths
What the number actually claims, what it doesn't, and the four sentences you need to read a result honestly without ever computing anything.
Topic
Articles on Minimum detectable effect
Everything we have published on Minimum detectable effect: guides, experiments and what we learned along the way.
6 articles
3 min read
More than two variants: when an A/B/C actually makes sense
Adding a third variant costs you a third of your sample and buys you a comparison you may not need. Three cases where it's worth it, and one very common case where it isn't.
3 min read
How to prioritise hypotheses when you can only run one test a month
ICE and PIE were designed for teams running twenty tests a quarter. When you get twelve a year, the scoring model has to change.
4 min read
How much traffic do you need for A/B testing?
The honest answer has three inputs and no marketing spin. Here's how to calculate it for your own site, and what to do when the number comes back too big.
4 min read
What to test first when your site doesn't have much traffic
Low traffic doesn't mean you can't experiment. It means you can only detect large effects — so you have to test the things capable of producing them.
2 min read
Sample size: how to know if your test is reliable
Sample size quietly ruins more experiments than any other factor. Learn the three variables behind it and how to know if your A/B test can actually reach a conclusion.
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