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PPHA-31000: Statistics for Public Policy I

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University of Chicago, Harris School of Public Policy (Harris)

PPHA-3100: Statistics for Public Policy I

Description: This course aims to provide a basic understanding of statistical analysis in policy research. Fundamental to understanding and using statistical analysis is the realization that data does not emerge perfect and fully formed from a vacuum. An appreciation of the provenance of the data, the way it was collected, why it was collected, is necessary for effective analysis. Equally important is an understanding of the nature of the statistical inference being attempted the course will distinguish between model-based and design-based inference. There will be some emphasis placed on sampling from finite populations and on data from survey research. The emphasis of the course is on the use of statistical methods rather than on the mathematical foundations of statistics. Because of the wide variety of backgrounds of participating students, the course will make no assumptions about prior knowledge, apart from arithmetic. For students with a strong technical background, the aim of the course is to increase their understanding of the reasoning underlying the methods, and to deepen their appreciation of the kinds of substantive problems that can be addressed by the statistical methods described. PP31000 or PP31200 required of all first-year students.

Faculty: Ben Keys

Source: Syllabus downloaded from http://harrisschool.uchicago.edu/course-description/31000/statistics-public-policy-i , 3 April 2014.

Teaching Topics Addressed in this Course, Organized by Public Management Subject

[TO BE DEVELOPED]

 

Commentary by the Atlas editors: The class titles and the headings in the bibliography in the Syllabus suggest a number of the potential topics to be developed for the Atlas:

  • Centre Spread, Normal Distribution
  • Describing Data: Correlation and Two-Way Tables
  • Sampling and Survey Design
  • Basic Probability
  • Conditional Probability
  • Random Variables and the Law of Large Numbers
  • Sampling Distributions for Counts and Proportions
  • Central Limit Theorem
  • Confidence Intervals
  • Tests of Significance and Power
  • Inference for Mean of a Population
  • Two-Way Tables and Chi-Square Tests
  • Regression

Page created by: Ian Clark on 3 April 2014. 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

Chicago Statistics I, 31000 Syllabus, Keys 2013.pdfChicago Statistics I, 31000 Syllabus, Keys 2013

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