**Select menu: Stats | Regression Analysis | Linear Models**

The Simple linear regression with groups downdown list option fits a sequence of models to data values that are classified into groups.

## Response variate

Specifies the name of the response (or y-) variate.

## Explanatory variate

Specifies the name of the explanatory (or x-) variate.

## Groups

Specifies a factor defining the different groups.

For an analysis of parallelism the first model to be fitted is a simple linear regression, ignoring the groups. Next the model is extended to include a different constant (or intercept) for each group, giving a set of parallel lines one for each group. Then, the final model has both a different constant and a different regression coefficient (or slope) for each group. The list adjacent to the **Groups** field lets you select between the types of regression model that you want to fit.

## Final model

For an analysis of parallelism, if the analysis shows that different intercepts are needed but not different slopes, you can use this option to select the final model and re-run the analysis to remove the interaction between the explanatory variate and the groups factor. Similarly, if different intercepts are not needed this option can be used to fit just the explanatory variate.

## See also

- Linear Regression for information on general options and other models
- Options for choosing which results to display
- Further Output for additional output subsequent to analysis
- Saving Results for further analysis
- Fitted Model for graphical display of the model
- Model Checking to generate diagnostic plots for model checking
- MODEL, FIT and ADD directives for fitting regression models with groups using the command language
- Quantile Regression menu
- Functional Linear Regression menu