Quantitative Evaluation for Public Policy (Session 2)
Course is Full
Course Description
Enrollment for this course is closed. We will only admit students from the waitlist if places become available. Please make other selections for your application.
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 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. You 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. You will also learn how to use a statistical software program to organize and analyze data. Most importantly, you 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.
Course Criteria
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.
Academic Interest
Social Sciences (e.g., history, sociology, business), Technology
Application Materials
A complete application includes a transcript, two short essays, a letter of recommendation, writing sample, application fee, and a submitted parent confirmation. If you are seeking need-based financial aid, you must indicate that in your application before it is submitted. Please refer to the Application Instructions for complete details.
Instructor(s)
Sheng-Hao Lo
Cost
$8,900
This course is completely full. Please choose another course instead. We recommend that you apply for more than one course on your application.
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