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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Why are decision trees a useful technique for segmentation?

A) Trees split the response into homogeneous groups, while maximizing the difference in the response of the groups.
B) Trees split the response into heterogeneous groups, while minimizing the difference in the response of the groups.
C) Trees split data into smaller cells which are decreasingly "pure".
D) Trees treat each split cell dependently based on earlier split decisions.

2. In SAS Visual Analytics, what is the purpose of creating an aggregated measure?

A) To calculate summary statistics for a measure
B) To replace dirty data with missing values
C) To combine multiple categories into fewer levels
D) To transform a categorical variable into a numerical one

3. In decision tree analysis, what is typically found on the y-axis of an icicle plot?

A) Depth of the tree
B) Feature values
C) Class labels
D) Impurity measures

4. Which modeling technique automatically includes missing values?

A) Linear regression
B) Generalized linear model
C) Logistic regression
D) Decision tree

5. When assigning variable roles for a decision tree, which role typically represents the target variable you want to predict?

A) Output
B) Predictor
C) Splitter
D) Input

Solutions: