Introduces students to concepts and techniques essential to the empirical analysis of public policy issues. Provides an introduction to probability, statistics, and decision analysis, emphasizing the ways in which these tools are applied to practical policy questions. Topics include: applied probability; decision making under uncertainty; working with data; statistical inference; and hypothesis testing. The course also provides students an opportunity to become proficient in the use of generative AI tools to effectively analyze quantitative data.
API-201 is required for MPP students and is a prerequisite to API-202. Attendance at TF sessions will be required every other week. This course may not be taken for credit with API-205 or API-209. MPA students can enroll in API-201 only with the permission of the API-201 course head and if admitted will be assigned to a section by the MPP faculty chair.