Calculate how long your A/B test needs to run to reach a target statistical power at a given significance level, based on:
- Baseline conversion rate and expected relative % change
- Traffic: daily traffic, traffic allocation, and allocation ratio
Configure your parameters and press Calculate to get a recommended number of days and power analysis charts.
What is Power Analysis?
Power analysis helps you determine:
- Sample size: How many participants you need to detect a meaningful effect
- Statistical power: The probability of detecting an effect if it exists (typically 0.8 or 80%)
- Effect size: The minimum difference you can detect with your sample size
- Significance level (α): The probability of a Type I error (false positive), typically 0.05
- Test duration: How many days your test needs to run based on daily traffic and number of buckets