Bivariate Data

This part extends the same data-first approach to relationships between two variables. It covers bivariate distributions, group comparisons, association statistics, linear and local regression, gradients and model fit, and the distinction between those tools and causal analysis. Throughout, we use real data in R to choose and evaluate bivariate models and to communicate what they show. We do this without making causal claims that the design cannot support.