Date of Award
1973
Degree Type
Report
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
Committee Chair(s)
Ronald V. Canfield
Committee
Ronald V. Canfield
Abstract
Many procedures have been proposed for analyzing and describing multivariate dependence structure.
Partial correlation, multiple correlation, canonical correlation, principal component and factor analysis are used to analyze the dependence structures of a multinormal population.
For a partial correlation analysis it is necessary to decide which variables are to be correlated and which of the remaining variables must be held constant.
Multiple correlation demands that one variable be dependent upon some or all of the remaining variates.
For a canonical correlation, the variables must be collected into two or more sets. The factor analysis technique is for explaining the covariances of the variables and the principal component technique is for explaining the variance of the variables.
The principal component technique consists of an orthogonal transformation of the coordinate axes of a multivariate system to new orientations.
Recommended Citation
Kim, Chong S., "Canonical Analysis of Several Sets of Variables" (1973). All Graduate Plan B and other Reports, Spring 1920 to Spring 2023. 1165.
https://digitalcommons.usu.edu/gradreports/1165
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