Better studies start
with honest assumptions.

Power analysis should support judgment—not replace it.

Sample-size calculators often return a precise number without showing how much that number depends on the inputs. StatPower is designed to do the opposite: connect the result to the expected effect, error rates, and practical limits of the planned study.

The goal is not to make every research design look simple. It is to make the first planning conversation clearer, earlier, and more defensible.

What guides the tool

A focused tool from DASS

StatPower is created by Data Analysis & Statistical Solutions, a research consulting practice supporting study design, statistical analysis, evaluation, training, and publication. DASS works with academic researchers, nonprofits, healthcare teams, public institutions, and technology companies.

The free calculator handles common early-planning questions. When a study includes clustering, repeated measures, attrition, multiple outcomes, unequal allocation, or uncertain effect sizes, DASS can develop a design-specific power analysis and reproducible rationale.

Use results as a planning aid

t tests use the exact noncentral t distribution, correlations use Fisher’s z transformation, and proportions use Cohen’s arcsine (h) approximation. t-test and proportion results match R’s pwr package exactly; correlation results agree closely and, at very small samples, err on the conservative side (slightly larger samples, slightly lower power). Results should still be checked against the intended analysis, realistic effect-size evidence, and the actual sampling design before they are used in a protocol, grant, preregistration, or publication.