How do we know whether a policy delivers its promised results or falls short? If it delivers, how do we know whether it was by chance or a true result that would replicate in a similar setting? If it is a true result, will it scale if implemented more broadly?
This course is designed for enterprising high school students who want to join the work at the frontiers of data analysis, using the tools that economists and other social scientists use to determine the causal effects of different actions and make more informed decisions. Students will be introduced to the basic toolkit of quantitative policy analysis, which includes probability theory, sampling, hypothesis testing, regression, experiments, differences in differences, and regression discontinuity. Students will also learn how to use a statistical software program to organize and analyze data. Most importantly, students will learn the principles of critical thinking essential for careful and credible policy analysis. The goals of this course will be realized through various course activities including lectures, labs, group assignments and final presentations.
Remote or Residential
Students should have completed Algebra 2 to be successful in this course.
Prior coding experience is not required; having some familiarity with coding (especially in R) would be helpful.
Current Grade / Education Level
Class Duration (CST)