Accelerated Stat for Pub Pol I

3 Credits · Level: Graduate, Juris Doctor, Undergraduate

This course provides the foundation for effective statistical analysis of policy data by introducing students to multivariate linear regression, with a particular emphasis on distinguishing causal effects from spurious relationships. By the end of the semester students will be able to: 1) Understand research methods and be able to formulate statistically testable hypotheses; 2) Interpret the results of multivariate linear regressions and think critically about the potential problems that arise when trying to draw conclusions from such results, including omitted variable bias, multicollinearity, interaction effects and transforming variables; 3) Understand maximum likelihood estimation for limited dependent variables; 4) Be comfortable coding in R for statistical projects. Tools include loops, functions and lists. This course is taught in R. As part of our effort to teach effective communication skills, students will make presentations about applications using techniques being studied. For MS-DSPP students only.