Fall 2013
Week 1
Thurs 8-29.
No Class Meeting

Week 2
Tues 9-3.
Course Overview, Introduction to Quantitative Methods [ppt]
Text: Chapter 1

Thurs 9-5.
Variables, Constructs, and Measurement

Week 3
Tues 9-10.
The Mean as a Statistical Model [ppt]
Text: Chapter 3.1 - 3.2
Optional: Anderson, The End of Theory, Wired Magazine 2008.

Thurs 9-12.
Normal Curves, Confidence Intervals, and the Central Limit Theorem
Text: Chapter 6

Week 4
Tues 9-17.
Research Problems [ppt]
Text: Chapter 7

Thurs 9-19.
Hypothesis Testing and Inference

Week 5
Tues 9-24.
Introduction to the R Environment [ppt] [R console from class]

Thurs 9-26.
Simple Graphs in R Commander [Rcmdr notes]
Text: Chapter 2
Assignment: PS 1 due Thurs 10-3

Week 6
Tues 10-1.
Principles of Data Visualization [ppt] [R script]

Thurs 10-3.
Data Visualization
Assignment: Lab 1 due Thurs 10-10

Week 7
Tues 10-8.
Probability Rules [ppt]
Thurs 10-10.
Common Assumptions in Statistics [ppt] [R script]
Assignment: PS 2 due Thurs 10-17

Week 8
Tues 10-15.
Correlation [ppt] [R script]

Thurs 10-17.
Chi-Square

Week 9
Tues 10-22.
Comparing Means [ppt] [R script]

Thurs 10-24.
Non-Parametric Tests of Difference

Week 10
Tues 10-29.
ANOVA [ppt] [R script]

Thurs 10-31.
ANOVA, continued

Week 11
Tues 11-5.
Experimental Design [ppt]

Thurs 11-7.
Natural Experiments
Assignment: Lab 2 due Thurs 11-14

Week 12
Tues 11-12.
Least Squares Regression [ppt] [R script]
Text: Chapter 12

Thurs 11-14.
Causal Inference in Data Analysis
Guest lecture by Prof. Jesse Anttila-Hughes, University of San Francisco

Week 13
Tues 11-19.
No class

Thurs 11-21.
No class

Week 14
Tues 11-26.
Multivariate Regression [ppt]

Thurs 11-28.
Thanksgiving Holiday

Week 15
Tues 12-3.
Multivariate Regression, Continued [R script]
Final Exam distributed (Due Friday 12-6 11:59pm)

Thurs 12-5.
Guest lecture by Mollie Epstein, University of California, San Francisco