Recitation sections are at the end of each week. Assignment are due after recitation during the week indicated in the table.

Week 1: Introduction  
1 Course overview; epistemological foundations; math review  
2 What's in a number?; basic numeracy; measurement  
Week 2: Planning numbers; descriptive statistics Problem set 1 due
3 The use of numbers in planning  
4 Variables; samples and populations; measures of central tendency  
Week 3: Talking about distributions  
5 Measures of variability  
Lab 1 Computer lab #1: getting to know Stata (or R); data management  
Week 4: Asking and answering questions with data Written assignment 1 due
6 Exploratory data analysis and visualization  
7 Logic, experiment, and the scientific method  
Week 5: Probability and the normal curve Problem set 2 due
8 Basic probability  
9 The normal curve; sampling  
Week 6: Inferential statistics  
10 Estimates and confidence intervals  
11 The idea of a statistical test; non-parametric tests  
Lab 2 Computer Lab #2: exploratory data analysis  
Week 7: Computers and data  
12 Midterm exam  
13 Statistical software; data management  
Week 8: Introduction to bivariate/multivariate data  
14 Cross-tabulations; χ2 tests  
15 Scatterplots; correlation; cause and effect; confounding variables  
Lab 3 Computer Lab #3: Statistical tests; scatterplots  
Week 9: Simple regression Written assignment 3 proposal due
16 Simple regression  
17 The assumptions of regression analysis  
Week 10: Multivariate regression  
18 Multivariate regression  
19 Review/slack; presentation and graphs  
Week 11: Particulars of planning data and questions Written assignment 2 due
20 The census  
Lab 4 Computer lab #4: Regression; computer clinic  
Week 12: Dealing with dollars; making decisions  
21 Talking about money  
22 Decision trees, expected utility, cost-benefit analysis  
Week 13: Review; slack; additional critical thinking Written assignment 3 due
23 Predictions and uncertainty; representing risk  
24 Return to research design; review