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Salvador Ascencio Pastora Photo

Salvador Ascencio Pastora

Appointment
Adjunct Lecturer in Public Policy

Jonathan Borck Photo

Jonathan Borck

Appointment
Adjunct Lecturer in Public Policy

Teddy Svoronos Photo

Teddy Svoronos

Appointment
Senior Lecturer in Public Policy

Charles Taylor Photo

Charles Taylor

Appointment
Assistant Professor of Public Policy

API-201

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: descriptive statistics; applied probability; decision making under uncertainty; statistical inference; and hypothesis testing. The course also provides students an opportunity to become proficient in the use of computer software widely used in analyzing quantitative data.

API-201 is required for MPP students and is a prerequisite to API-202. The R sections teach students to use the statistical programming language R, move more quickly through the material, and prepare students to independently produce their own empirical analyses of data. The non-R sections teach students to use Excel for statistical analysis, and prepare students to analyze and interpret, but not necessarily to independently produce, empirical analyses of policy issues. 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.