Course description

Students taking this class form the staff of the consulting lab, a free statistical consulting service in Sequoia Hall. In addition, students attend weekly lectures on Friday to discuss consulting cases and various statistical techniques that arise frequently in consulting. Some of the slides from these meetings appear below and serve as very high level introductions to the respective topics. Consultants need to know about the existence of available methods even if they have not mastered their use.

References

Lecture slides from Friday sessions and links to various resources are posted below for quick reference.

Mixed models

Link Description
pdf Slides from Friday meeting
html Introductory R-bloggers post on lme4
pdf Documentation on the lme4 package
pdf Theory and computation of lme4
html Introduction to generalized linear mixed models

Time series

Link Description
pdf Slides from Friday meeting
html Quick-R overview of time series methods
pdf Slightly longer overview. Start in chapter 2
html A longer reference using additional/different packages
html R-bloggers post on a Bayesian method for causal inference

Multiple testing

Link Description
pdf Slides from Friday meeting
html Wikipedia article
html Brief overview of two of the most common methods
html (Advanced) Lecture notes from Stats 300C. See roughly Lectures 6-14
pdf A Bayesian alternative

Non-parametrics, Permutations, and Bootstrap

Link Description
pdf Slides from Friday meeting
html, html General wikipedia articles
html Bootstrap wikipedia article
html Minitab support on nonparametric tests
pdf Efron's 1977 Rietz lecture on the bootstrap

Causal inference

Link Description
pdf Slides from Friday meeting
html, html, html Wikipedia articles
html Book by Miguel Hernan and Jamie Robins. See first few chapters
html Books by Paul Rosenbaum. The "design" one is easier. Library.