Linear Regression Analysis in the Social Sciences (Houston, TX)

Instructor(s):

  • Sunny Wong, University of Houston
  • Patrick Shea, University of Houston

This course is designed for participants to develop quantitative research skills with applications to social science topics. Participants will gain an overview of research design, data management, and statistical analysis and interpretations of research findings. The course will be centered around several main topics covering the basic analysis of ordinary least squares (OLS), the technique of estimating bivariate and multivariate regression models, the overall fitness of a regression equation, and the hypothesis and diagnostic testings, and more. This course takes the "learning by doing" approach by discussing the major themes in regression analysis with detailed examples, which show how the subject works in practice using Stata.

Prerequisites: The level of the course will be approximately that of Gujarati and Porter's Basic Econometrics.

Software: Stata

Financial support of up to $1,000 per workshop is available for eligible students. In order to determine if you qualify for funding, send a personal statement of purpose, letter of recommendation from an advisor/colleague, and a copy of your unofficial transcript to Pablo Pinto (ppinto2@uh.edu), Director of the University of Houston Center for Public Policy, and Scott Mason (smason@uh.edu), Program Manager 2 at the University of Houston Hobby School of Public Affairs. The deadline for submitting this request is Friday, April 19.

Fee: Members = $1700; Non-members = $3200

Tags: regression, linear regression, OLS, ordinary least squares

Course Sections

Section 1

Location: University of Houston -- Houston, Texas

Date(s): May 13 - May 17

Time: 9:00 AM - 5:00 PM

Instructor(s):

  • Sunny Wong, University of Houston
  • Patrick Shea, University of Houston

Syllabus: