Fall 2019 - 59510 - PA 397 - Introduction to Empirical Methods for Policy Analysis - FALL SEMESTER ONLY | LBJ School of Public Affairs | The University of Texas at Austin

Fall 2019 - 59510 - PA 397 - Introduction to Empirical Methods for Policy Analysis - FALL SEMESTER ONLY

Introduction To Empirical Methods for Policy Analysis

Overview

PA397 introduces students to fundamental management science and statistical techniques that are essential for making and evaluating public policy.  The course also provides an opportunity to become proficient in the use of computer software that is widely used in analyzing quantitative data.

Learning Outcomes

By the end of the semester, students should have a firm understanding of…

  • the logic underlying descriptive statistics, basic probability, sampling, inferential statistics, regression, decision theory, and mathematical programming;
  • the importance of judgment in drawing inferences from data and building mathematical models; and
  • the “ins and outs” of STATA and Excel Solver

In addition, students should be able to…

  • interpret the results of statistical analyses and mathematical models used in public policy research done by others;
  • use appropriate statistical analyses and mathematical models in their own work; and
  • present the results of statistical analyses and mathematical models effectively.

Grading

Grades will be based on a final exam (35%), mid-term exam (25%), and four problem sets (40%).

Class Preparation

PA397 is a challenging course that moves rapidly.  Preparation for each class is essential.  Lectures will be most productive if everyone has done the required reading and worked through the relevant examples in the text before class.

The required reading list is relatively short to allow students more time to work problems and do their own analyses.  Students will learn more by puzzling over a problem than by rereading chapters or trying to memorize formulas.

Students are encouraged to form regular study groups to work together on problem sets and preparing for class.  Groups of two to four students work best.  With more participants, some members invariably do a lot more listening and following than thinking and contributing. 

Problem sets should reflect each student’s own work and understanding of the material.  Students working in groups are expected to submit their own assignments and acknowledge with whom they have worked.  In other words, although you are encouraged to work together in determining the approach to a problem, your final analysis and the presentation of results must be your own work. 

Lectures and Discussion

I encourage you to help make this course interesting and relevant to you.  An important part of this process is asking questions, participating in class discussions, and sharing your relevant experiences.

Course Materials

  1. Introduction to Statistics, Susan F. Wagner, Collins Reference (1992) or National Learning Corporation (1992).  ISBN-10: 0064671348 or 0837374464. ISBN-13: 978-0064671347 or 978-0837374468.  The text is required and is available from a variety of online used booksellers or as a reading packet at the UT Co-op. 
  2. STATA/IC 15 software: In as much as STATA will be an integral part of the problem sets, and the exams will require students to be able to read and interpret STATA output, students are recommended to purchase either a six-month ($45) or one-year ($89) license of STATA/IC 15 through the GradPlan.  To purchase STATA/IC 15, visit https://www.stata.com/order/new/edu/gradplans/student-pricing/ or call 1-800-782-8272.  Alternatively, students may use the computers in the 2nd floor computer lab – STATA/IC 15 should be installed on all of the computers in the lab.
  3. MS-Excel spreadsheet software with Solver add-in.

The text and software will be supplemented as needed by a variety of online materials, handouts, and the course slides prepared by the instructor.

M.P.Aff
M.P.Aff-DC
Class Schedule: 
TH 9:00AM to 12:00PM
SRH 3.B7
Final Exam Date: 
Thursday, Dec 12, 2019
Final Exam Location: 
SRH 3.122