Commentary by the Atlas Editors: This landmark course aims to provide students with the ability to understand and critically assess quantitative research that sheds light on public policy issues. In order to further their practical understanding of quantitative research methods, students learn how to use statistical software (in this case STATA) to conduct their own basic quantitative research.
Students use STATA to perform regression analysis and other types of quantitative research throughout this course. Course evaluation is based largely on series of nine assignments (eight minor assignments and one major assignment) for which students are required to use their knowledge of STATA to analyze data and assess the public policy implications. In addition to these assignments, students take a final written exam that tests knowledge of all course material.
The material taught in this course can be divided into the following broad topics:
1.) Confidence Intervals and Hypothesis Testing (weeks one and two)
2.) Linear Regression (weeks 3, 4 and 5)
3.) Multiple Regression: (weeks 6 and 7. Includes learning about: dummy variables, least squares assumptions, omitted variables bias, binary dependent variables and internal validity).
4.) Randomized Experiments and Difference-in-Differences studies.
5.) Panel Data.
Page created by: Ben Eisen and Matthew Seddon, last updated 28 April 2013. 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.