Quantitative Analysis Practicum

This course provides policy analysis PhD students with practical skills and tools to conduct quantitative analyses. Through this practicum, students will learn how to translate their knowledge on statistical theories and policy analysis tools into a completed applied analysis. By the course's completion, students should be able to:

1. Accurately plan out a research project step-by-step and execute it.
2. Use code to run a complete analysis.
3. Provide useful feedback to colleagues on code quality, analysis approaches, and presentation of results.

Calendar

Week	Date	Day	Slides	Articles	Code	Resources
1	1/8	Monday	Design Planning		Basics of R Ex 1. Investigate LEMAS Ex 2. Process IPUMS data	ROS: Appendix A and HWT: Chapter 1 - 2
1	1/10	Wednesday		Tong, 2019
2	1/15	Monday	MLK Day
2	1/17	Wednesday	Sourcing Data	Knox, Lowe, & Mummolo, 2020	Simple DAGs Ex 3. Using DAG to generate synthetic data	ROS:Chapter 16
3	1/22	Monday	Data Processing		Ex 4. Webscrapping Ex. 5 UCR Data Prep	ROS:Chapter 12
3	1/24	Wednesday		Anscombe, 1973 Steegen et al., 2016
4	1/29	Monday	Data analysis and descriptive Models		Ex. 6 Analyzing hours worked in CPS	ROS: Chapter 2
4	1/31	Wednesday		Case & Deaton, 2015 Gelman & Auerbach, 2016
5	2/5	Monday	Causal Models		Ex. 7 Panel data models Ex. 8 Simulation models GOF plots	ROS: Chapter 18 - 21 and Appendix B
5	2/7	Wednesday		Blair et al., 2019
6	2/12	Monday	Displaying Results		Intro to ggplot
6	2/14	Wednesday		Gelman, Fagan, & Kass, 2007
7	2/19	Monday	[Interpreting results]			ROS:Chapter 11
7	1/21	Wednesday		King, Tomz, & Wittenberg, 2000 Collinson et al., 2023	[Goodness-of-Fit] [Sensitivity Analyses]
8	2/26	Monday	[Peer Review]		[Simulations]	ROS: Chapter 5
8	2/28	Wednesday		Witteman et al., 2019
9	3/4	Monday	[Workshopping]			EW
9	3/6	Wednesday
10	3/11	Monday
10	3/13	Wednesday