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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What conditions might make models less comparable in SAS Visual Statistics?

A) If they are both logistic regression models
B) If they have different learning rates
C) If they use the same dataset and response variable
D) If they have similar AUC values

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

A) By using a weighted sum of all decision rules in the tree
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 averaging the values of all leaf nodes

3. Refer to the exhibits:
Exhibit 1:

Exhibit 2:

An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.
Why are there 5 cluster IDs in Exhibit 2 based on these settings?

A) Cluster Matrix Visible Roles setting is 5.
B) There are observations with missing values.
C) Parallel Coordinates Visible Roles setting is 5.
D) Variable Standardization has been chosen.

4. In linear regression, what does the coefficient of determination (R-squared) measure?

A) The impact of outliers on the model
B) The goodness of fit of the model to the data
C) The p-value associated with the intercept term
D) The degree of multicollinearity among predictors

5. Refer to the exhibit:

A cluster has been created with four variables selected on the roles tab.
Select the set of Parallel Coordinates Properties that would display the image in the exhibit.

A)

B)

C)

D)

Solutions: