STATS 601 - Analysis of Multivariate and Categorical Data
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Waitlist Capacity:
Advisory Prerequisites:
STATS 600.
May be repeated for a maximum of 8 credit(s).
Primary Instructor:

This is an advanced introduction to the analysis of multivariate and categorical data. Topics include: 1) dimensional reduction techniques, including principal component analysis, multidimensional scaling and extensions; 2) classification, starting with a conceptual framework developed from cost functions, Bayes classifiers, and issues of over-fitting and generalization, and continuing with a discussion of specific classification methods, including LDA, QDA, and KNN; 3) discrete data analysis, including estimation and testing for log-linear models and contingency tables; 4) large-scale multiple hypothesis testing, including Bonferroni, Westphal-Young and related approaches, and false discovery rates; 5) shrinkage and regularization, including ridge regression, principal component regression, partial least squares, and the lasso; 6) clustering methods, including hierarchical methods, partitioning methods, K-means, and model based clustering.

STATS 601 - Analysis of Multivariate and Categorical Data
Schedule Listing
001 (LEC)
26STATS PhD only
MW 2:30PM - 4:00PM
002 (LAB)
Th 8:30AM - 10:00AM
NOTE: Data maintained by department in Wolverine Access. If no textbooks are listed below, check with the department.

Hastie, Friedman, and Tibshirani, The elements of statistical learning. Available online
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