This page implements an online version of John Kruschke's Bayesian estimation supersedes the t-test (BEST), a Bayesian model that can be used where you classically would use a two-sample t-test. BEST estimates the difference in means between two groups and yields a probability distribution over the difference. From this distribution we can take the mean credible value as our best guess of the actual difference and the 95% Highest Density Interval (HDI) as the range were the actual difference is with 95% credibility. It can also be useful to look at how credible it is that the difference between the two groups is < 0 or > 0.

To try it out just enter some data below or run with the data that is already entered, the heights in m of the winning team of the 2012 NBA finals (group 1) and the winning team of Stanley cup 2012 (group 2). Data can be entered in almost any way, separated by spaces, commas, newlines, etc.

The MCMC method used is an adaptive Metropolis-within-Gibbs sampler described by Roberts and Rosenthal (2009). Everything is implemented in javascript and runs in the browser. If the output looks strange try to increase the number of burn-in steps and the number of sample steps.