Select the output to be generated initially in a regression analysis – the same information can also be displayed after the analysis, using the *Further output* dialog. You can also request that no constant term is included in the model: this will affect only the parameterization of factor effects, if there are factors in the model; but if not, it will constrain the regression to pass through the origin.

For a general regression model, you can also control the maximum order of interaction to be generated when you use model-formula operators like *. The default is to include all interactions, up to those involving nine variates or factors. (You cannot ask for more than nine.)

## Display

Model |
Details of the model that is fitted. |

Summary |
Summary analysis-of-variance. |

F-probability |
F probabilities for variance ratios. |

Correlations |
Correlations between the parameter estimates |

Fitted values |
Table containing the values of the response variate, the fitted values and residuals from the regression. |

Estimates |
Estimates of the parameters in the model |

t-probability |
t probabilities for the parameter estimates the fitted values, standardized residuals and leverages. |

Confidence intervals |
Confidence intervals for the parameter estimates. The confidence limit can specified as a percentage using the Confidence limit for estimates (%) field. |

Accumulated |
Analysis of variance table containing a line for each change in the fitted model. |

Wald tests |
Wald and F tests for dropping terms from a regression. Where the regression contains a model function (e.g. polynomial, smoothing spline or locally weighted (loess) terms), the Wald tests cannot be calculated. |

## Estimate constant term

Specifies whether to include a constant in the regression model. In simple linear regression this omits the intercept, in other words the fitted line is constrained to pass through the origin.

## Graphics

Lets you generate default plots when you run a regression analysis. **Plot residuals** will produce diagnostic plots of the residuals. Following simple linear regression you can also use **Plot fitted model** to generate a graph of the fitted model.

## See Also

- Further Output
- Change Regression Model
- Saving Results
- Save Individual Regression Terms dialog
- Save regression results in a spreadsheet
- Fitted Model for graphical display of the model
- Model checking
- Predictions from Simple Linear Regression
- Predictions from Simple Linear Regression (grouped)
- Predictions from Multiple Linear Regression
- Predictions from Multiple Linear Regression (grouped)
- Predictions from General Linear Regression
- Plot Table of Predictions
- Least Significant Intervals Plot Options dialog
- Change Regression Model
- Multiple Comparisons for Predictions options
- Linear Regression for information on general options and other models
- Simple Linear Regression
- Simple Linear Regression (with Groups)
- Multiple Linear Regression
- Multiple Linear Regression (with Groups)
- General Linear Regression
- Polynomial Regression
- Smoothing Spline
- Locally Weighted Regression
- Quantile Regression menu
- Functional Linear Regression menu
- Generalized Linear Models menu
- Standard Curves menu