What n do I need for this experiment?
Work out how many samples you need
Power analysis, done before the experiment rather than after.
Power analysis connects four quantities: the effect size you care about, your significance threshold, the power you want (conventionally 80%), and n. Fix any three and the fourth follows. The hard part is the effect size, which has to come from pilot data, a published study, or an honest decision about the smallest difference that would matter biologically.
That last option is underrated. "A 20% change is the smallest I would act on" is a defensible basis for a sample size calculation, and it makes the experiment answer a question you actually have.
Post-hoc power — computing power from the effect you observed, after a non-significant result — is circular and uninformative. It is a recognised statistical error, not a rescue for an underpowered study.
What to use
- Power and sample size
How many replicates you need — worked out before the experiment, not after.
Built inNo upload - G*Power
Power analysis and sample size calculation for the standard tests.
ExternalUniversität DüsseldorfFree - R and RStudio
The statistical environment nearly all biological methods are written for.
ExternalR Foundation / PositFree