Stop 10 · A/B Testing & ExperimentationTopics · 2/8
Sample Size & Test Duration
Part of the Data Analyst Roadmap
In short
Calculating how many users (and how long) you need before a test has enough statistical power to detect a real effect — running a test too briefly is one of the most common experimentation mistakes.
How to learn this
- 1Use a free sample size calculator for a hypothetical test scenario.
- 2Learn how baseline conversion rate and minimum detectable effect both affect required sample size.
- 3Understand why low-traffic features are especially hard to test reliably.
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