Sociology 504: Social Statistics

Princeton University
Spring 2009
Lecture: Tuesday and Thursday: 10:00am - 11:30am (Location: Wallace 165)
Lab: Thursday: 11:30am - 1:00pm (Location: Stokes Library Computer Lab)
Instructor: Matthew Salganik
Preceptor: Dennis Feehan

This course provides an introduction to social statistics.

There will be weekly problem sets given out each Tuesday and due the following Tuesday. Many of the problem sets will involve the statistical package R. I know that the choice of R will lead to difficulties in the beginning of the semester, but there will be big payoffs later as you become more familiar with it. Regarding R, we will start slowly and assume that you do not have any programming experience. In addition to problem sets, students will be expected to complete a final project of some sort. These final projects will be due Tuesday, May 12th (Dean's Day); no extensions will be given.

There required texts are:

We will also read chapters from the following books, but these will be available on Blackboard:

Below are the readings assignments for each week. You should come to class having looked at this material and you should read it roughly in the order listed. I will distinguish the Fox books by calling them Fox and Fox (R book).

Week 1: Introduction and mathematical background

Week 1 Lab: Introduction to R

Week 2: Visualizing data

Week 2 Lab: Visualizing data

Week 3: Intuition of regression and transforming data

Week 3 Lab: Intuition of regression and transforming data

Week 4: Regression and multivariate regression

Week 4 Lab:

  • Fox (R book), Chapter 4.1.
  • Week 5: Statistical inference for regression

    Week 5 Lab:

    Week 6: Introduction to causal inference

    Week 6 Lab:

    Week 7: Dummy variable regression and interactions

    Week 7 Lab:

    Week 8: ANOVA

    Week 8 Lab:

    Week 9: Statistical theory for linear models

    Week 9 Lab:

    Week 10: Regression diagnostics

    Week 10 Lab:

    Week 11: Logit, probit, and generalized linear models

    Week 11 Lab:

    Week 12: Review, criticisms, and other approaches

    Week 12 Lab: Project presentations

    Additional material