Lecture Notes

SES #	TOPICS
1	Course Overview (PDF)
2	Statistical Models (PDF)
3	Bayesian Models (PDF)
4	Decision Theoretic Framework (PDF)
5	Prediction (PDF)
6	Sufficiency (PDF)
7	Exponential Families I (PDF)
8	Exponential Families II (PDF)
9	Methods of Estimation I (PDF)
10	Methods of Estimation II (PDF)
11	Bayes Procedures (PDF)
12	Minimax Procedures (PDF)
13	Unbiased Estimation and Risk Inequalities (PDF)
14	Convergence of Random Variables Probability Inequalities (PDF)
15	Limit Theorems (PDF)
16	Asymptotics I: Consistency and Delta Method (PDF)
17	Asymptotics II: Limiting Distributions (PDF)
18	Asymptotics III: Bayes Inference and Large-Sample Tests (PDF)
19	Gaussian Linear Models (PDF)
20–25	Generalized Linear Models (PDF)
26	Case Study: Applying Generalized Linear Models (PDF)

Course Info