COURSE SCHEDULE[1]

This schedule will be updated regularly. Given the flexible nature of the

course, the schedule will extend only a few weeks beyond the current session.

	Session Topic and associated slides	Readings (RWG = Hamilton, Regression with Graphics; RCAR = Fox, An R and S-Plus Companion…; DAUG = Gelman and Hill, Data Analysis Using Regression…)
Week 1	Introduction; “How to survive this class” & Introduction to R	Before class readings: review this web page. RCAR 1-2
Week 2	Review of (a) OLS regression; (b) partial regression coefficients; and (c) regression diagnostics.	RWG 3-4 RCAR 3-4
Week 3	Models with intercept and slope interactions	RWG pp. 84-91 RCAR pp. 126-135 DAUG pp. 34-36
Week 4	Introduction to hierarchically structured models
Week 5	Interacted OLS Models
Week 6	Basic Multi-Level Models
Week 7	Elaborating Multi-Level Models
Week 8	Estimating ML Model Fit
Week 9
Week 10	Simulations in R; Running simulations in R; script for the lecture is here
Week 11	Models and Interpretations
Week 12
Week 13
Week 14

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[1][1] Dates for each topic are approximate. Check the schedule frequently for updates.