Statistical Power & Type I/II Errors (2D)

Every hypothesis test balances two ways to be wrong: a Type I error (rejecting a true null, rate α) and a Type II error (missing a real effect, rate β). This 2D simulator plots the null and alternative sampling distributions as two overlapping curves, shaded by which decision region each slice falls in, with two live mini-charts tracing power against sample size and effect size. Drag sample size, effect size and significance level — or grab the critical line itself — and watch the split between false positives, misses and true detections update in real time, the same mechanics an A/B test or a clinical trial's power analysis runs on before a single subject is measured.