| Dr. Richard Evans | Dr. Benjamin Soltoff | TBD (TA) | TBD (TA) | |
|---|---|---|---|---|
| [email protected] | [email protected] | |||
| Office | 250 Saieh Hall | 249 Saieh Hall | ||
| Office Hours | W 2:30-4:30pm | Th 2-4pm | ||
| GitHub | rickecon | bensoltoff |
- Meeting day/time: MW 11:30-12:50pm, Saieh Hall, Room 247
- Lab session: W 5-5:50pm, Saieh Hall, Room 247
- Office hours also available by appointment
- TAs: TBD
This course focuses on applying computational methods to conducting social scientific research through a student-developed research project. Students will identify a research question of their own interest that involves a direct reference to social scientific theory, use of data, and a significant computational component. The students will collect data, develop, apply, and interpret statistical learning models, and generate a fully reproducible research paper. We will identify how computational methods can be used throughout the research process, from data collection and tidying, to exploration, visualization and modeling, to the final communication of results. The course will include modules on theoretical and practical considerations, including topics such as epistemological questions about research design, writing and critiquing papers, and additional computational tools for analysis.
| Assignment | Points | Quantity | Total points |
|---|---|---|---|
| Proposal | 10 | 1 | 10 |
| Literature review | 15 | 1 | 15 |
| Methods/initial results | 15 | 1 | 15 |
| Peer evaluations of posters | 2 | 5 | 10 |
| Poster presentation | 30 | 1 | 30 |
| Final paper | 40 | 1 | 40 |
| Problem set | 10 | 3 | 30 |
| Total Points | 150 |
If you need any special accommodations, please provide us with a copy of your Accommodation Determination Letter (provided to you by the Student Disability Services office) as soon as possible so that you may discuss with me how your accommodations may be implemented in this course.
| Date | Day | Topic | Readings | Assignment due dates |
|---|---|---|---|---|
| Mar. 27 | M | Overview of term | ||
| Mar. 29 | W | Reproducibility in science | ||
| Apr. 3 | M | Abstract/intro/conclusion | ||
| Apr. 5 | W | Proposal presentations | Written proposal | |
| Apr. 10 | M | Abstract/intro/conclusion | ||
| Apr. 12 | W | Data section of paper | ||
| Apr. 17 | M | Data section of paper | ||
| Apr. 19 | W | Theory section of paper | Data PS | |
| Apr. 24 | M | Computation section of paper | Theory section | |
| Apr. 26 | W | Computation section of paper | ||
| May 1 | M | Results/experiment section of paper | Computation PS | |
| May 3 | W | Diagnostic tests for OLS/GLM | ||
| May 8 | M | Interaction terms | ||
| May 10 | W | Missing data and multiple imputation | ||
| May 15 | M | Multilevel data | Hodgepodge PS | |
| May 17 | W | p-hacking | Methods/initial results | |
| May 22 | M | Frequentist vs. Bayesian schools of inference | ||
| May 24 | W | Effective presentations (poster/slides) | ||
| May 29 | M | No class (Memorial Day) | ||
| May 31 | W | In-class poster presentations | ||
| Jun. 1 | Th | Poster presentations | ||
| Jun. 5 | M | Final paper |
All readings are required unless otherwise noted. Adjustments can be made throughout the quarter; be sure to check this repository frequently to make sure you know all the assigned readings.