#### 15.13.1 Syntax

         REGRESSION
                 /VARIABLES=var_list
                 /DEPENDENT=var_list
                 /STATISTICS={ALL, DEFAULTS, R, COEFF, ANOVA, BCOV}
                 /SAVE={PRED, RESID}

The `REGRESSION` procedure reads the active dataset and outputs statistics relevant to the linear model specified by the user.

The `VARIABLES` subcommand, which is required, specifies the list of variables to be analyzed. Keyword `VARIABLES` is required. The `DEPENDENT` subcommand specifies the dependent variable of the linear model. The `DEPENDENT` subcommand is required. All variables listed in the `VARIABLES` subcommand, but not listed in the `DEPENDENT` subcommand, are treated as explanatory variables in the linear model.

All other subcommands are optional:

The `STATISTICS` subcommand specifies the statistics to be displayed:

`ALL`
  All of the statistics below.
`R`
  The ratio of the sums of squares due to the model to the total sums of squares for the dependent variable.
`COEFF`
  A table containing the estimated model coefficients and their standard errors.
`ANOVA`
  Analysis of variance table for the model.
`BCOV`
  The covariance matrix for the estimated model coefficients.

The `SAVE` subcommand causes pspp to save the residuals or predicted values from the fitted model to the active dataset. pspp will store the residuals in a variable called ‘`RES1`’ if no such variable exists, ‘`RES2`’ if ‘`RES1`’ already exists, ‘`RES3`’ if ‘`RES1`’ and ‘`RES2`’ already exist, etc. It will choose the name of the variable for the predicted values similarly, but with ‘`PRED`’ as a prefix.