Effect size
The smallest difference or relationship that would matter in the real world.
Free study-planning tool
Plan a study that can
answer the question.
Explore how sample size, effect size, and uncertainty work together—before you collect the data.
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01 / Study design
Power planner
02 / Your result
64per group
You need 128 participants total to have an 80% chance of detecting a medium-sized difference.
Well powered for this effect
Power curveHow recruitment changes your chance of detecting the effect
80%The honest part: This result is only as credible as your expected effect. Use prior evidence or the smallest effect worth detecting—not a convenient guess.
Power, plainly
Four numbers.
Four numbers.
One design decision.
Power analysis connects the signal you care about to the evidence your study can realistically produce.
Sample size
How many independent observations your design needs—not simply how many are available.
Alpha
Your tolerated false-positive rate. Lower alpha demands stronger evidence.
Power
Your chance of detecting the effect if it truly exists. It equals 1 − β.
Built for defensible planning
A calculator should show its work.
StatPower uses transparent large-sample approximations for early planning. It is most useful before data collection, paired with a justified effect size and an analysis plan that matches your design.
- ✓ Inputs never leave your browser
- ✓ Reporting sentence included
- ✓ Clear assumptions and limitations
Complex design?
The right calculation starts with the right model.
Clusters, repeated measures, attrition, multiple outcomes, or uncertain effect sizes can change the answer substantially. Get a design review from DASS before the study is locked.
Discuss your study