These datasets and codes present regression analyses used in management studies to introduce management scholars to data science. First, I describe the backdoor criterion, which is helpful for variable selection to identify causal effects. Next, I describe interaction models and hierarchical Bayesian models as the regression models in which effects vary across individuals. Finally, I introduce causal effect estimation using machine learning to use regression models for prediction.