1. The R option on the MODEL statement in PROC REG in SAS refers to:

Ranking the results.
Right justifying the results.
Generating the studentized residuals.
Imposing an implied restriction.
Requesting data reduction.

2. The following statement is not true:

For basic regression analyses, the dependent variable should be interval or ratio.
To calculate and print the predicted values, use the P option in the MODEL statement.
When a plot of the residuals against the predicted values for a straight-line model shows a definite curved pattern, this indicates you need to add a quadratic term to the model.
Residuals are defined as the observed values minus the actual sample values.
If a studentized (standardized) residual is 3.0 or larger in absolute value, then you can consider the observation a probable outlier.

3. Useful data plots associated with regression analysis include all the following except:

Plotting the dependent variable against each of the independent variables.
Plotting the fitted values of the dependent variable along the regression line against their predicted values.
Plotting the residuals against each of the independent variables in the model.
Plotting the residuals against potential independent variables that have not yet been included in the model.
Plotting the residuals against the predicted vaues from the regression.

4. Plotting cannot be used to find out if:

A relevant independent variable has been left out of the regression.
A quadratic rather than a linear relationship would be more appropriate.
A time sequence can be detected in the data.
Outliers can be identified in the data.
The residual sum of squares has definitely been minimized.

5. When you use PROC REG interactively, the following statement does not necessarily end the procedure:

DATA;
ENDSAS;
PROC PLOT;
QUIT;
RUN;