Listed in: Mathematics and Statistics, as STAT-240
Nicholas J. Horton (Section 01)
Inger Persson (Section 01)
Real world experiments often provide data that consist of many variables. When confronted with a large number of variables, there may be many different directions to proceed, but the direction chosen is ultimately based on the question(s) being asked. In biology, one could ask which observed characteristics distinguish females from males in a given species. In archaeology, one could examine how the observed characteristics of pottery relate to their location on the site, look for clusters of similar pottery types, and gain valuable information about the location of markets or religious centers in relation to residential housing. This course will explore how to visualize large data sets and study a variety of methods to analyze them. Methods covered include principal components analysis, factor analysis, classification techniques (discriminant analysis and classification trees) and clustering techniques. This course will feature hands-on data analysis with statistical software, emphasizing application over theory. Four class hours per week.
Requisite: STAT 111 or 135. Limited to 20 students. Fall semester. Professor Persson.
Section 01
Tu 11:30 AM - 12:50 PM MERR 131
Th 11:30 AM - 12:50 PM MERR 131
Section 01
W 12:00 PM - 12:50 PM MERR 131
This is preliminary information about books for this course. Please contact your instructor or the Academic Coordinator for the department, before attempting to purchase these books.
| ISBN | Title | Publisher | Author(s) | Comment | Book Store | Price |
|---|---|---|---|---|---|---|
| An Introduction to Applied Multivariate Analysis with R | Springer | Everitt and Hothorn | Amherst Books | TBD |
These books are available locally at Amherst Books.