## Introduction

Whereas traditional correspondence analysis analyzes a table, *multiple correspondence analysis* analyzes the variables themselves; for example, a multi-response question with 11 categories is analyzed as 11 categorical variables. It is essentially a form of factor analysis for categorical data. You should use it when you want a general understanding of how categorical variables are related. This article describes how to run a Multiple Correspondence Analysis in Displayr.

## Requirements

- Multiple categorical variables to use as inputs to the Multiple Correspondence Analysis. As an example, we'll use 5 different variables from a political survey: voting in the 2008 and 2012 US elections, approval of President Trump, age, and gender.

## Method

1. From the toolbar menu, select **Anything > Advanced Analysis > Dimension Reduction > Multiple Correspondence Analysis**.

2. Select the categorical variable inputs from the **Input Variables** drop-down list in the object inspector on the right.

3. Click the **Calculate** button to generate the output.

## See Also

How to do Traditional Correspondence Analysis

How to Add Images to a Correspondence Analysis Map

How to do Correspondence Analysis of a Square Table

How to Create a Quality Table from a Correspondence Analysis

How to do 3D Correspondence Analysis

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