This course provides a foundation in the principles and practice of quantitative social science, with a focus on building tools to make descriptive, causal, and predictive inferences.

Logistics

We meet twice a week, alternating lectures on Tuesdays and labs on Thursday. Both sessions require laptops that run R and RStudio

Lecture

Tuesdays 10:30-11:50 am

Labs

Thursdays 10:30-11:50 am

Assignments

Due on Canvas

Location

Smith-Buonanno Hall G01

Zoom

Office Hours

Paul | Tuesdays 1-3 pm
111 Thayer St Rm 339

Maya | Thursdays 2:30-4:30 pm
111 Thayer St Rm 309

Schedule

	Lecture	Labs	Solutions	Assignments
Week 0
Introductions
Week 1
Data & Measurement
Week 2
Data Visualization
Week 3
Causation -- Experiments
Week 4
Causation -- Observational Studies
Week 5
Bivariate Regression
Week 6
Multiple Regression
Week 7
Regression Extensions
Week 8
Probability - Random Variables & Distributions
Week 9
Probability - Limit Theorems
Week 10
Inference -- Confidence Intervals
Week 11
Inference -- Hypothesis Testing
Week 12
Workshop
Week 13
Presentations