Course Syllabus

O’Neill School of Public and Environmental Affairs
SPEA-V 370 Research Methods and Statistical Modeling
sect. 3897

A downloadable link to the pdf or docx copy of the complete course Syllabus is available  on the Home  or Modules page located in the left-sidebar navigation.

Course Description

This course will introduce the student to the basic methods, issues, analytical techniques, and ethical considerations of evaluation research.

Course Content

The course consists of two modules linked with each other: (i) Statistical (econometric) modeling, and (ii) Research Methods. The first module of the course covers basics of the regression analysis and use of statistical software. Students will be introduced to intermediate-level perspective on statistical concepts and techniques for analyzing and modeling modern data with emphasis on practical and applied modeling aspects. The module content includes estimating the parameters of econometric models, testing hypotheses, making inference and forecasting. Multivariate regression analysis is one of the primary tools for statistical modeling for purposes of policy analysis, program evaluation, simulation of systems, and general forecasting. Students will be actively involved with computer exercises using the Stata econometrics program available for installation to personal computers PC and Macs as well  as in every STC Computer Lab. Throughout the course students will use Stata to implement a series of econometrics exercises designed to provide experience with various tests and estimation procedures. In parallel with Stata programing, if time allows, I will introduce programming in   Gretl or R  -- free and open source statistical software. The second module of the course is designed to develop each student's ability to design an empirical study within the ethical constraints of human research and to understand the results of empirical research presented in professional journals. We will also discuss how to use and avoid misuse of GenAI for data analysis. Modeling examples will be drawn from the fields of  law, public policy, business, education and others with a special emphasis on social issues and policy analysis research (e.g. environmental concerns, global climate change, cultural issues, COVID-19 etc.).

Course Objectives and Learning Outcomes

The purpose of this course is to introduce students to basic statistical concepts and techniques. At the end of this course, you should be able to:

  • read social science and policy analytical materials; draw information from different sources;
  • know how to design a valid policy/social study/experiment;
  • recognize and disclosure some of the misuses of statistical analysis;
  • develop basic econometric models, carry out an adequate statistical analysis for the basic types of data, and interpret and present results;
  • use Stata software for policy analysis/empirical studies (Prior knowledge of Stata is not required);
  • use (and avoid misuse) of GenAI as research assistant.

Detailed learning outcomes for each week of the class are included on the Canvas Modules pages and Handouts.

Course Meeting information

Class 3897 meets on Mo, Tu, We, and Th  (MTWR) at 2:30-4:10 pm in Room  A223 (SPEA building)

Textbook

Required textbook: Damodar Gujarati, Essentials of Econometrics, 5/e, Sage, 2021 is available via IU eTexts (Unizin Engage) located in the left-sidebar navigation (no purchase required). 

Additional readings will be posted via Canvas.