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API-201: Quantitative Analysis and Empirical Methods

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Harvard Kennedy School

API- 201: Quantitative Analysis and Empirical Methods

Description: This course introduces students to concepts and techniques essential to the analysis of public policy issues. It 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; basic probability; conditional probability; Bayes' rule; decision making under uncertainty; expected utility theory; sampling design; 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.

Faculty: Kerrie Nelson (API-201A, Fall 2012), Christopher Robert (API-201B, Fall 2012), Erich Muehlegger (API-201C, Fall 2012), John Friedman (API-201D, Fall 2012)

Source: At http://http://www.hks.harvard.edu/degrees/teaching-courses/course-listing (accessed 13 February 2013)

 

Additional course description from the syllabus

Our goal is that by the end of this course you will be able to:

1. Take a data set and a broad descriptive policy question (such as “what has happened to incomes in the US in the last 30 years?”), figure out what statistical analysis would be most appropriate to answer the question, conduct such an analysis, identify what are the most salient findings/patterns that emerge from the data, and present the findings in a way that is accessible to policymakers.

2. Identify real world policy situations in which the tools of probability can be used, identify which tools are most relevant to inform courses of action in those real world situations, and critically consume policy analysis in which probability is used.

3. Critically consume policy studies/papers/reports in which statistical analysis is used.

4. Use the decision analysis framework as one tool to make personal and professional decisions, and to think about policy problems.

The course content is divided into five broad units: Descriptive Statistics, Probability, Statistical Inference, Sampling and Survey Design, and Decision Analysis. Section A of the course also provides you with an opportunity to become proficient in the use of both Stata and Excel, as tools to analyze quantitative data.

Section A will follow a similar syllabus to Sections B, C, and D, but assumes a greater level of mathematical facility. It will proceed somewhat faster than the other sections, allowing more time for applications, in-depth discussions, and a number of advanced topics. Section A will use two statistical software packages, Stata and Excel, to conduct data analysis throughout the semester, whereas Sections B, C and D will focus on the use of Excel. Students are encouraged to talk with the course faculty members in order to determine whether section A is a better fit.

Required textbook

Introduction to the Practice of Statistics by Moore, McCabe and Craig. W.H. Freeman, 7th Edition.

Readings for the Decision Analysis unit are packaged into a course-pack available from the Course Materials Office. These readings are excerpts from Smart Choices: A Practical Guide to Making Better Life Decisions (Hammond, Keeney, Raiffa) and A Primer for Policy Analysis (Stokey, Zeckhauser).

Recommended textbooks

How to Lie With Statistics. Darrell Huff, Irving Geis. W. W. Norton & Company; Reissue edition, 1993. ISBN: 0393310728. This book is a classic that has been in print for over 50 years. It has great, though sometimes dated, examples of how policy makers, journalists, and business people abuse and misuse statistics. (optional)

Open Intro Statistics, David Diez, Christopher Barr, Mine Çetinkaya. You may do the pre-class readings from this textbook instead of from the required textbook Electronic version of the textbook is available for free at www.openintro.org. Paperback copies may also be purchased for under $7 on CreateSpace or Amazon.

Mathematical Statistics with Applications. Dennis Wackerley, William Mendenhall, Richard Scheaffer. Duxbury Press; 7th edition, 2007. ISBN: 0495110817. This book helps to provide more advanced mathematical details for methods that we will be discussing. (optional)

The Cartoon Guide to Statistics. Larry Gonick, Woollcott Smith. HarperResource; 1st HarperPerennial ed edition, 1994. ISBN: 0062731025. This book relates to the last part of the course. It is a nice lay-person’s guide to decision analysis by three prominent leaders in the field. (optional)

Commentary by the Atlas editors: The class titles provide provisional teaching topics for two Atlas subjects:

Quantative Methods for Public Management

Descriptive Statistics

Probability Concepts

Bayes' Rule

Application: Public Pensions in Mexico

Discrete Distributions

Continuous Distributions

Statistical Inference for a Single Mean

Statistical Inference for a Single Proportion

Statistical Inference for Two Proportions

Statistical Inference for Two Means

Paired Data

ANOVA and Multiple Comparisons

Multivariate Analysis

Chi-Square Test

Sampling

Survey Design

Randomized Trials

Decision Sciences for Public Management

Decision Analysis (3 classes)

Page created by: Ben Eisen, 17 February 2013, updated by Ian Clark 23 February 2012. The content presented on this page, except in the Commentary, is drawn directly from the source(s) cited above, and consists of direct quotations or close paraphrases.

 

 Syllabus

API-201D.pdfAPI-201D
API-201C.pdfAPI-201C
API-201B.pdfAPI-201B
API-201A.pdfAPI-201A

Important Notices
© University of Toronto 2008
School of Public Policy and Governance