MACS 30200 - Perspectives on Computational Research (Spring 2017)

	Dr. Richard Evans	Dr. Benjamin Soltoff	Daniel Hedblom (TA)	Laila Noureldin (TA)
Email	[email protected]	[email protected]	[email protected]	[email protected]
Office	250 Saieh Hall	249 Saieh Hall	248 Saieh Hall	Harris School (Cafe)
Office Hours	W 2:30-4:30pm	Th 2-4pm	M 1-3pm	F 11:30-1:30
GitHub	rickecon	bensoltoff	hedblomdaniel	lailanoureldin

• Meeting day/time: MW 11:30-12:50pm, Saieh Hall, Room 247
• Office hours also available by appointment

Course description

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.

Grades

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

Students will turn assignments in via their own public GitHub repository named MACS30200proj. The directory structure of this repository should be the following.

• github.com/yourgithubhandle/MACS30200proj
  • ProblemSets
    • PS1
    • PS2
    • PS3
  • Proposal
  • LitReview
  • Theory
  • MethodsResults
  • Poster
  • FinalPaper

Disability services

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.

Course schedule (lite)

Date	Day	Topic	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	Proposal slides & present
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	Computational results section of paper	Literature review section
Apr. 26	W	Computational results section of paper
May 1	M	Workshop papers/office visits
May 3	W	Diagnostic tests for OLS	Computation PS
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. 4	Su		Final paper due at 11:59pm

References and Readings

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.

• Diagnostic tests for OLS/GLM
  • Ch 3.3.3 in An Introduction to Statistical Learning
• Interaction terms
  • Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political analysis, 63-82.
• p-hacking
  • Significant
  • Wasserstein, R. L., & Lazar, N. A. (2016). The ASA's statement on p-values: context, process, and purpose. Am Stat, 70(2), 129-133.
  • "Science Isn't Broken" by Christie Aschwanden. FiveThirtyEight.
  • Beall, A. T., & Tracy, J. L. (2013). Women are more likely to wear red or pink at peak fertility. Psychological Science, 0956797613476045.
  • "Too Good to Be True" by Andrew Gelman. Slate.
  • "Response by Jessica Tracy and Alec Beall to my critique of the methods in their paper, 'Women Are More Likely to Wear Red or Pink at Peak Fertility'" by Andrew Gelman.