GSBA 604 – FALL 2018

To find all the class materials for this class please click on this dropbox link.

Below is an non-exhaustive list of links to some of the class topics:

CONTENTS	DOWNLOAD LINK
Syllabus	Link
R-labs	Link
Class Notes	Link
Homework	Link

The class notes are prepared based on the following books and resources:

Module 1 and 2:

• J.J. Faraway. Practical Regression and Anova using R
• G. James, D. Witten, T. Hastie, and R. Tibshirani. An introduction to statistical learning. New York: springer. 2013.
• J. Friedman, T. Hastie, and R. Tibshirani. The Elements of Statistical Learning. New York: Springer series in statistics.
• Sengupta, D. and Jammalamadaka S. R. Linear Models: An integrated approach.

Module 3:

• Agresti. Foundations of Linear and Generalized Linear Models, Wiley 2015.
• J.J. Faraway. Extending the Linear Model with R.

Module 4:

• Gelman and J. Hill. Data Analysis Using Regression and Multilevel/Hierarchical Models.
• D. Rubin and G. Imbens. Causal Inference for Statistics, Social and Biomedical Sciences: An Introduction.

In addition I have used note-extracts from my graduate school days spanning several courses such as Stats 306A taught by Brad Efron, Iain Johnstone and Art Owen across different years and Stats 315A taught by Rob Tibshirani and Trevor Hastie.