Correspondence Analysis (CA)

Correspondence analysis is a statistical technique used to analyze the associations between categorical variables in large datasets. It aims to uncover patterns and relationships between the categories of different variables by visualizing them in a low-dimensional space, typically a two-dimensional plot.

This method is particularly useful when dealing with categorical data, such as survey responses, where variables are not numerical but represent different categories or levels. Correspondence analysis transforms the categorical data into a graphical representation, allowing for easier interpretation of relationships between variables.

Benefits of Correspondence Analysis:
  •  Visual Interpretation: Correspondence analysis provides a visual representation of the relationships between categorical variables
  •  Dimension Reduction: Similar to factor analysis, correspondence analysis reduces the dimensionality of the data while preserving the key relationships between variables.

Applications of Correspondence Analysis

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