# Row and column contributions for Simple Correspondence Analysis

Find definitions and interpretation for every statistic that is provided for row and column contributions for simple correspondence analysis.

## Qual

Quality (Qual) is the squared distance of the point from the origin in the chosen number of dimensions divided by the squared distance from the origin in the space defined by the maximum number of dimensions. Minitab calculates a quality value for each row and each column in the contingency table.

### Interpretation

Use the quality values to determine the proportion of the row inertia or column inertia represented by the components. Quality is always a number between 0 and 1. Larger quality values indicate that the row or column is well represented by the components. Lower values indicate poorer representation. The quality values for the rows and columns can help you interpret the components.

## Mass

Mass is the total of the matrix of relative frequencies for a row or column in the contingency table. The mass of a row is the sum of all the frequencies in the row divided by the sum of all the frequencies in the contingency table. The mass of a column is the sum of all the frequencies in the column divided by the sum of all the frequencies in the contingency table.

### Interpretation

Use the mass to determine the proportion of each row or column category. Larger mass values indicate that the row or column has a higher relative frequency. The total mass for all the row categories or all the column categories equals 1 (100%).

## Inert

Cell inertia is the chi-squared value in the cell divided by the total frequency for the contingency table. The row inertia (Inert) is the sum of the cell inertias for the row. The column inertia (Inert) is the sum of the cell inertias for the column. The sum of all the cell inertias is the total inertia, or simply the inertia.

### Interpretation

Use row inertia and column inertia to assess associations between categories and contributions to variation in the data. Higher values generally indicate a stronger association and greater deviation from the expected values.

## Coord

Minitab calculates row and column principal coordinates (Coord) for each component. The row principal coordinates are the principal coordinates of each row profile in terms of the principal component. The column principal coordinates are the coordinates of each column profile in terms of the principal component.

To visually display the points defined by the row and column principal coordinates, use a symmetric plot or asymmetric plot.

## Corr

Minitab calculates row and column correlation values. The row correlation value represents the contribution of the component to the inertia of the row. The column correlation value represents the contribution of the component to the inertia of the column. Correlation values range from 0 to 1.

### Interpretation

Use the correlation value to interpret each component in terms of its contribution to inertia. Values close to 1 indicate that the component accounts for a high amount of inertia. Values close to 0 indicate that the component contributes little to inertia.

## Contr

The contribution (Contr) of each row or column to the inertia of each component.

### Interpretation

Use the contribution values for the rows and/or columns to interpret the components.

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