Summary

In this chapter, we delved into regression analysis, causal inference, and DAGs. We learned about the basics of linear regressions and logistic regressions. We also walked through DAGs and causal inference and finished on counterfactual analysis.

We have learned the basics of regression models and the differences between a linear regression and a logistic regression. Now you know how to create a DAG for your regression, choose the right regression model, and estimate and interpret the parameters.

We will pick this topic back up in Chapter 13, when we discuss experimentation. But for now, we will turn our attention to time series forecasting and the application of regression analysis to time data.