It appears that there is an imbalance in what many beginning bayesian data analysts think about BDA. From casual observation and discussions, I’ve noticed a tendency for people to equate bayesian methods with computing bayes factors; that is, testing (usually null) hypotheses using bayesian model comparison.
Today, we’ll take a look at creating a specific type of visualization for data from a within-subjects experiment. You’ll often see within-subject data visualized as bar graphs (condition means, and maybe mean difference if you’re lucky.) But alternatives exist, and today we’ll take a look at within-subjects scatterplots.
2017 will be the year when social scientists finally decided to diversify their applied statistics toolbox, and stop relying 100% on null hypothesis significance testing (NHST). A very appealing alternative to NHST is Bayesian statistics, which in itself contains many approaches to statistical inference. In this post, I provide an introductory and practical tutorial to Bayesian parameter estimation in the context of comparing two independent groups’ data.