Mathematical Sciences 807
Applied Multivariate Analysis
Instructor: Calvin L. Williams, Ph.D.
Text: Methods of Multivariate Analysis
Author : Alvin C. Rencher
Course Objective
Multivariate data through experimentation and observation occur quite
often in engineering, business, social sciences, as well as biological and
physical sciences. This is a course in applied multivariate data analysis.
It will cover descriptive and graphical methods for continuous multivariate
data, the multivariate normal, multivariate tests of means, covariances
and equality of distributions, univariate and multivariate regression
and their comparisons, multivariate analysis of variance,
covariance structure models, and discrimination and classification.
Furthermore it should be emphasized that this course and hence the
chosen text, is designed around the application of multivariate
techniques to continuous data, time allowing we will endeavor to
discuss methods of discrete multivariate analysis from prepared class
notes.
Students will learn how to use statistical software to facilitate the
understanding of the foundations of multivariate analysis. Statistical
packages will include R,Matlab, and SAS.
Course Syllabus:
Syllabus
Computing Information
Useful SAS Code
Useful Matlab Code
Useful R Code
Data Sets....Updated and Corrected Frequently. Updated April 20, 2011
Disclaimer: These data sets are copyrighted and are available for use only
by students in Mathematical Sciences 807 Applied Multivariate Statistics. Any other use
is forbidden.
Helpful Statistics Sites
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Author:
Calvin L. Williams,
Mathematical Sciences-Clemson University,
Clemson University
Last updated:
August 20, 2011
Send Comments to :
calvinw@clemson.edu