About Our Calculators
What Makes a Good
Sample Size Calculator?
A sample size calculator is one of the most critical tools in a researcher's methodology. The required sample size determines whether your study has enough statistical power to detect a real effect, and whether your confidence intervals are tight enough to be meaningful. Too few participants risks a Type II error — missing a true effect. Too many wastes resources and exposes unnecessary participants to research risk.
Most free online sample size calculators only handle a single study type — usually a basic survey proportion formula. ResearchToolsLab's free sample size calculator supports five distinct study designs: survey research using the Cochran formula with finite population correction, two-group experiments using Cohen's d effect size, clinical trials with dichotomous and continuous endpoints (Kelsey/Schlesselman 1982), Pearson correlation studies using Fisher's z-transformation, and population prevalence estimation.
Critically, every formula result is accompanied by the exact mathematical formula used, all variable definitions, and the original academic reference. Researchers can cite Cochran (1977), Cohen (1988), or Schlesselman (1982) directly — not a website — which is the academically correct approach for research proposals and journal submissions.
The calculator also addresses the most commonly overlooked aspect of sample size planning: attrition adjustment. Recruiting exactly your minimum analysable sample is a mistake — if participants drop out or fail eligibility screening, your final sample will be underpowered. ResearchToolsLab applies a sequential adjustment: screening exclusions first, then post-enrollment dropout, giving you the correct recruitment target rather than just the analysis minimum.