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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Select the best distribution to model with linear regression.

A)

B)

C)

D)

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

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

3. What does a Group-by Variable enable you to do in SAS Visual Statistics?

A) Fit a model for every value of a measure's distribution.
B) Leverage informative missingness for measure and category variables.
C) Fit a model for each data segment defined by one or more category variables.
D) Use variable selection.

4. How are predictions formulated for a decision tree when a new data point is presented to the model?

A) By averaging the values of all leaf nodes
B) By calculating the Euclidean distance to all tree nodes and selecting the closest one
C) By following a path through the tree to a leaf node and returning the majority class or mean value of that node
D) By using a weighted sum of all decision rules in the tree

5. What can you interpret from the Assessment panel in a decision tree analysis?

A) The decision boundaries between leaf nodes
B) The feature importance for each variable in the tree
C) The tree's training and validation performance metrics
D) The tree's structural properties, such as depth and number of nodes

Solutions: