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