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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What does a ROC chart help assess in model comparison?

A) The correlation between predictor variables
B) The trade-off between true positives and false positives at different thresholds
C) The distribution of residuals in the models
D) The stability of model predictions

2. You would like to compare multiple models that you've built in SAS Visual Statistics.
Which parameters must be the same for all models being compared? (choose 3)

A) Event Level
B) Assessment Bins
C) Response Variable
D) Model Type
E) Link Function
F) Data Source

3. Which statement is TRUE regarding a generalized additive model (GAM) in SAS Visual Analytics?

A) Specification of a spline effect is optional.
B) A larger maximum degrees of freedom for the univariate spline term enforces a less complex fit.
C) GAM assumes a strict linear relationship between the predictors and the response function.
D) The roughness penalty controls the balance between goodness of fit and the roughness of the spline curve.

4. When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?

A) Binomial distribution with a logit link function
B) Exponential distribution with a square root link function
C) Poisson distribution with a log link function
D) Normal distribution with an identity link function

5. In linear regression, what does a high p-value for a predictor variable suggest?

A) The predictor is not relevant for the model.
B) The predictor has a strong linear relationship with the response.
C) The predictor is highly significant for the model.
D) The predictor is a categorical variable.

Solutions: