The goal of this course is to provide students with the tools to conduct quantitative analyses of data derived from a two group RCT. By the end of the course, students should be able to use these tools to: choose the right research question; use appropriate data and statistical methods to address the question; and interpret results. We will model the impact of different randomly assigned treatments on outcomes using the linear regression model, and consider the properties of the ordinary least squares (OLS) estimator of the parameters of the linear regression model. As we will see, the properties of the OLS estimator depend on the nature of the unobserved random component of the model (the “error term”). We will we will consider the implications for our estimator of clustering and heteroskedasticity in the error term, and correlation of the error term with treatment choice.