API 201C - Quantitative Analysis & Empirical Methods I





API-201 introduces a range of quantitative tools commonly used to inform public policy issues. It covers
descriptive statistics, probability theory, decision analysis, statistical inference, and regression analysis,
with an emphasis on the ways in which they are applied to practical policy questions. Our goal is that by
the end of this course you will be able to:

  1. Frame a broad descriptive policy question (such as “what has happened to crime rates in the U.S. in the past 30 years?”), figure out the most appropriate statistical analysis to answer the question, conduct the analysis using real world data, identify the most salient findings/patterns that emerge from the data, and present the findings in an effective manner to policymakers.
  2. Become skilled in the use of probability and decision analysis tools to better tackle real world personal and policy decisions involving uncertainty.
  3. Critically consume policy studies/papers/reports in which statistical analysis is used.

The course content is divided into five broad units: Descriptive Statistics (2 classes), Probability (7 classes),
Decision Analysis (3 classes), Statistical Inference (9 classes), and Regression Analysis (2 classes). The
course also provides you with an opportunity to become proficient in the use of Excel as a tool to analyze
quantitative data.

This course is required for first-year students in the MPP program. First-year MPP students with prior
coursework in statistics can place out of the course entirely by taking an exemption exam at the start of the
semester. The only way to exempt from API-201 is to demonstrate a high level of mastery on the exemption
exam. Students not enrolled in the MPP program may be admitted with permission of the relevant instructor.

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