What is Canonical Correlation Analysis? State the similarity and difference between multiple regression and canonical correlation.

Canonical Correlation Analysis (CCA) is a statistical technique used to measure the relationship between two sets of variables. In economics, CCA is often employed to explore the associations between two sets of economic indicators or variables, with the aim of identifying underlying patterns or relationships. 

Similarities between Multiple Regression and Canonical Correlation Analysis:

1. Multivariate Analysis: Both multiple regression and canonical correlation analysis are multivariate statistical techniques, meaning they involve the analysis of multiple variables simultaneously.

2. Relationship Exploration: Both methods aim to explore relationships between variables. While multiple regression examines the relationship between a dependent variable and several independent variables, canonical correlation analysis assesses the relationship between two sets of variables.

3. Parametric Approach: Both techniques assume a parametric relationship between variables. Multiple regression assumes a linear relationship between the dependent and independent variables, while __________ ___ ______ _________ ____.
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