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Canonical Correlation Analysis

Canonical Correlation Analysis

Canonical Correlation Analysis:

The purpose of canonical correlation analysis is to explain or summarize the relationship between two sets of variables by finding a linear combinations of each set of variables that yields the highest possible correlation between the composite variable for set A and the composite variable for set B. One or more additional linear combinations are then formed for each variable set in an attempt to further explain the residual variance that is not explained by the initial correlation.

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Courses Using This Term

Multivariate Statistics
This course will teach you key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis, and classification.
Principal Components and Factor Analysis
In this course, you will learn how to make decisions in building a factor analysis model – including what model to use, the number of factors to retain, and the rotation method to use.
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