Instructor: Alexander Podkul, Ph.D.
Meeting Times: Wednedsay 6:30p - 9:00p
Email: arp52@georgetown.edu
Office Hours: By appointment or announcement (in-person or virtual)
Teaching Assistant: Alexandra Oderman
Email: alo55@georgetown.edu
Office Hours: Monday, 2:00PM – 4:00PM and by appointment (virtual)
To download a .pdf version of the syllabus, please visit Canvas.
This class is the second course in a three-part quantitative methods sequence for Master of Public Policy students at the McCourt School of Public Policy. There are three main goals for this course: 1) for students to understand how to estimate multiple linear regressions; 2) for students to gain exposure to the statistical models appropriate for use with dichotomous dependent variables; and 3) for students to learn how to present original, rigorous quantitative research findings to a professional audience. Additionally, those taking the course will become familiar with the Stata statistical software package for exploring data sets, estimating models, and presenting interpretable results. Students will leave the course as better consumers and producers of statistical analyses related to public policy.
There are two required textbooks for this course:
All other readings will be available for download on the course website. Additional suggested text resources to supplement scheduled course readings can be found under the “Resources” section of the course website.
| Assignment | Share of Final Grade |
|---|---|
| Midterm Examination | 20% |
| Final Examination | 30% |
| Data Project | 20% |
| Problem Sets | 20% |
| Class Participation | 10% |
For all assignments, tardy work without an approved extension from the course instructor will not be accepted.
Students are permitted to use laptops in the classroom, especially considering our frequent use of Stata for in-class supplemental examples. Use of other electronic devices is prohibited absent need.
The course professor will be available for office hour appointments by appointment and by announcement throughout the semester. Office hours are available both in-person and virtually. To request an appointment, send an e-mail to the instructor at arp52@georgetown.edu including a few possible meeting times.
If a course meeting is canceled due to inclement weather, closures related to Covid-19, or other unforeseen circumstances, the session will be made up electronically via an online lecture at the regularly scheduled course meeting time. Instructional continuity plans will be communicated following the school’s announcement of cancellation via email as soon as possible. When course meetings are held via Zoom, students are expected to have their cameras turned on to facilitate in-class discussion. If for some reason it is not possible to pivot to a virtual session, course content for that session will be delivered via asynchronous format later in the semester. Any changes to regularly scheduled course meetings will be communicated by Canvas Announcement.
If you believe you have a disability, then you should contact the Academic Resource Center (arc@georgetown.edu) for further information. The Center is located in the Leavey Center, Suite 335 (202-687-8354). The Academic Resource Center is the campus office responsible for reviewing documentation provided by students with disabilities and for determining reasonable accommodations in accordance with the Americans with Disabilities Act (ADA) and University policies. For more information, go to http://academicsupport.georgetown.edu/disability
McCourt School students are expected to uphold the academic policies set forth by Georgetown University and the Graduate School of Arts and Sciences. Students should therefore familiarize themselves with all the rules, regulations, and procedures relevant to their pursuit of a Graduate School degree. The policies are located at: http://grad.georgetown.edu/academics/policies
Considering the course syllabus, lectures, handouts, and problem sets as intellectual property, it is requested that students refrain from sharing course materials in any electronic or paper format without permission. Though sharing materials with others in class is acceptable, posting them online is unacceptable. If students have any questions, do not hesitate to reach out to the course instructor.
Additional notes pursuant to additional administrative policies are located on the Canvas in the Syllabus Appendix.
| Week | Topic | Notes | |
|---|---|---|---|
| January 19, 2022 | 1 | Course Introduction | |
| January 26, 2022 | 2 | Bivariate Regression and Introducing Indicator Variables | |
| February 2, 2022 | 3 | Multiple Regression and Gauss Markov | Problem Set #1 Due |
| February 9, 2022 | 4 | Goodness of Fit and Diagnosing Models | |
| February 16, 2022 | 5 | Interactions | Problem Set #2 Due |
| February 23, 2022 | 6 | Transformations, Quadratics, Functional Forms | Problem Set #3 Due |
| March 2, 2022 | 7 | MIDTERM EXAMINATION | |
| March 9, 2022 | NO CLASS (Spring Break) | ||
| March 16, 2022 | 8 | Heteroskedasticity | |
| March 23, 2022 | 9 | Binary Dependent Variables (1) | Problem Set #4 Due + Data Proj. Check-In |
| March 30, 2022 | 10 | Binary Dependent Variables (2) | Problem Set #5 Due |
| April 6, 2022 | 11 | Sampling and Weighting | Data Proj. Check-In |
| April 13, 2022 | 12 | Predictive Models | |
| April 20, 2022 | 13 | Missing Data and Other Data Issues | Data Project Due |
| April 27, 2022 | 14 | Applied Research for Policy Analysis | |
| May 6, 2022 | FINAL EXAM |
Any changes to the above schedule will be communicated to students during class sessions.