Package: bstrap 0.0.1

bstrap: Obtain and plot bootstrap sampling distributions of the sample mean

Many common tests assume sufficient normality of the data distribution, with the received wisdom that if the sample size is "large", the normality doesn't matter so much (because of the Central Limit Theorem). It is difficult to judge the normality is good enough, or whether the sample size is big enough. A better way to investigate is to obtain a bootstrap sampling distribution of the sample mean (by taking repeated bootstrap samples), and to assess that distribution for normality. If it is, the normal-theory test will work; if not, not.

Authors:Ken Butler [aut, cre]