Summary • Uncertainty intervals are an important part of communicating statistics. • Bootstrapping a sample consists of creating new data sets of the same size by resampling the original data, with replacement. • Sample statistics calculated from bootstrap resamples tend towards a normal distribution for larger data sets, regardless of the shape of the original data distribution. • Uncertainty intervals based on bootstrapping take advantage of modern computer power, do not require assumptions about the mathematical form of the population and do not require complex probability theory.
