Korrespondenzanalyse

Korrespondenzanalyse, also known as correspondence analysis (CA), is a statistical technique used to explore and visualize relationships between categorical variables. It is particularly useful for understanding how different categories within two or more variables are associated. The primary goal of CA is to represent the rows and columns of a contingency table as points in a low-dimensional space, typically two dimensions, such that the proximity of points reflects the strength of their association.

The input for correspondence analysis is a contingency table, which displays the frequency distribution of two or more categorical variables. The analysis then transforms this table into a set of coordinates for each row and column category. These coordinates are then plotted on a perceptual map, where distances between points indicate the degree of correspondence. For example, if two row categories are close together on the map, it suggests they tend to occur with similar column categories. Conversely, if a row category is close to a column category, it indicates a strong association between them.

Correspondence analysis is widely applied in various fields, including marketing research, social sciences, and ecology, for tasks such as market segmentation, understanding brand perceptions, and analyzing survey data. It helps to identify patterns and structures within complex categorical data that might not be apparent through simple inspection of the contingency table. The interpretation of the resulting map is crucial, with researchers looking for clusters of points and their relative positions to draw meaningful conclusions about the relationships between variables.