Clinical Trial Power & Sample Size Simulator

This simulator explores the core statistical decision behind every randomized controlled trial: how many patients does a study need to reliably detect a real treatment effect? Set a treatment effect size and sample size per arm, choose a significance threshold, and watch simulated patients render as a 3D swarm split into control and treatment arms beneath two theoretical bell-curve distributions whose overlap represents the risk of a missed effect. Enrolling patients and running the trial draws a genuine random sample and computes a real two-sample Student's t-test p-value, while live readouts track statistical power, the sample size needed for conventional 80% power, and the observed mean difference — the same power-analysis math biostatisticians use to size real clinical trials before recruitment begins.