Probability
and Statistics
and Statistics
POLI_SCI 403
Plan for today
Course topic
Who are we and why are we here?
Course overview
Lab 0
About this course
First in the PhD methods sequence:
POLI_SCI 403: (Introduction to) Probability and Statistics
POLS_SCI 405: Linear Models (Wilson)
POLI_SCI 406: Quantitative Causal Inference (Seawright)
Methods electives this year
- Fall: Small-N (Mahoney)
- Spring: Experiments (McGrath)
- Year-long: Statistical Computing Workshop (Diaz)
This course
Statistical inference: Using data we have to understand something for which we do not have data
Sample questions
- What is the proportion of people who support criminalizing abortion?
- What is the relationship between economic development and democracy?
- Do voter ID laws affect turnout?
This course
Statistical inference: Using data we have to understand something for which we do not have data
Topics: Probability, estimation, inference, linear regression, maximum likelihood, causal inference
Theme: Make minimal assumptions
Important links
Syllabus and slides: gustavodiaz.org/ps403
Assignments: github.com/gustavo-diaz/ps403
Submit work: canvas.northwestern.edu/courses/256213
Meetings: cal.com/gustavodiaz
Who are we and why are we here?
Instructional team
Gustavo Diaz
Assistant Professor of Instruction in Political Science
Email: gustavo.diaz@northwestern.edu
Website: gustavodiaz.org
Office: 2001 Sheridan Rd, suite 3152
Mikhail Turchenko
PhD Student in Political Science
Email: mturchenko@u.northwestern.edu
Website: msturchenko.com
Office: 2001 Sheridan Rd, suite 3169
You (again)
- Name
- Pronouns
- Discipline + intended subfield/research area
- Favorite food/artist/book/place
Course overview
Textbook
DO NOT BUY
DIGITAL COPY AVAILABLE THROUGH LIBRARY SUBSRIPTION
OR
Additional readings linked in syllabus
Computing
R + RStudio for lab assignments and in-class demos
Local installation strongly recommended
Consider posit.cloud as backup
Other software allowed, no support guaranteed
Assigments
Participation
Lab assignments (8 total, due Fridays 11:59 PM)
Replication paper (due December 9 9:00 AM)
Contract grading
Participation (satisfactory/unsatisfactory)
Labs (satisfactory/unsatisfactory/fail)
Paper (outstanding/satisfactory/unsatisfactory/fail)
Canvas rubric
0: Unsatisfactory
1: Satisfactory
2: Outstanding
NA: Fail
Baseline contract (B+)
- Complete Lab 0
- Be late on no more than one lab assignment
- Submit final paper before deadline
- Complete 6 out of 8 labs
- Complete final paper
- Satisfactory participation mark
Improving your grade
A-
- Complete all labs
OR
- Outstanding final paper
Improving your grade
A
- Complete all labs
AND
- Outstanding final paper
Weekly workload
- ~3 hour lecture
- ~1 hour TA section
- One book chapter
- 1-2 articles/videos
- One lab assignment