Bootstrap Confidence Interval Calculator

About this calculator

The bootstrap, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic — here, the mean — by repeatedly resampling your observed data with replacement and recalculating the statistic on each resample, thousands of times. Unlike a traditional confidence interval that assumes an underlying normal distribution and relies on the t- or z-distribution, the bootstrap makes no such assumption, drawing the interval directly from the spread of resampled means using the percentile method.

This calculator takes your raw data, a chosen confidence level, and a number of resamples, then returns the resulting bootstrap confidence interval for the mean. Statisticians and data scientists working with small, skewed, or otherwise non-normal samples, and researchers who want a distribution-free alternative to the classical confidence interval use it when the usual normality assumptions are questionable or hard to verify.