Advanced Methods in Biostatistics 1 (140.751)

First term objectives: Random vectors, Multivariate normal distribution, Distributions of quadratic forms, Least squares estimation, Gauss Markov theorem, Orthogonal structures, Generalized least squares, Estimable functions, Hypothesis testing, Simultaneous confidence intervals, Departures from assumptions, Diagnostics.

Text: Franklin A. Graybill, Theory and Application of the Linear Model, Wadsworth, 2000.

Useful links: [ General Course Info | Chuck Rohde's Notes | Introduction to R (CRAN) | Introduction to R (Ingo) | Karl Broman's R Page | Julian Faraway's Book ]



Date N R H C Topic
September7 Introduction; Review of linear algebra and matrices
12 Random vectors
14 The multivariate normal distribution
19 Distribution of quadratic forms
21 Least squares estimation
26 Design matrices of less than full rank
28 Orthogonal structure in the design matrix
October3 Generalized least squares
5 Estimable functions
10 Hypothesis testing
12 Hypothesis testing
17 Hypothesis testing
19 Hypothesis testing
24 Review
26 Final

N: Notes R: Reading H: Homework C: Code