Course · Teaching
Data Analysis for the Social Sciences
A hands-on introduction to quantitative reasoning for sociology students — from research design through regression — taught in R, with the emphasis on questions rather than machinery.
Course
CodeSOC 334
TermFall 2026
Credits3
LevelUndergraduate
MeetsTue/Thu 12:15
RoomPowdermaker 252
Overview
This course teaches the craft of drawing careful conclusions from social data. Students learn to frame a question, choose a measure, describe a distribution, reason about uncertainty, and fit and interpret a regression — doing each by hand in R on real public datasets. No prior programming or statistics is assumed.
Objectives
- Translate a social question into a measurable, testable claim.
- Summarize and visualize distributions honestly.
- Reason about sampling, uncertainty, and inference.
- Fit, interpret, and critique linear regression models.
- Communicate quantitative findings in plain language.
Modules
01Research Design & MeasurementFrom questions to variables; validity and reliability.Weeks 1–202Describing DataDistributions, summary statistics, and honest graphics.Weeks 3–403Sampling & InferenceSampling distributions, standard errors, confidence intervals.Weeks 5–604Linear RegressionFitting, interpreting, and checking models.Weeks 7–905Communicating ResultsTables, figures, and writing for non-specialists.Weeks 10–12
