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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. How can you export score code generated by SAS Visual Statistics for a trained model?

A) By exporting it as a PDF document
B) By copying and pasting it into a text editor
C) By exporting it as a standalone script file
D) By printing it directly from the SAS Visual Statistics interface

2. What is unsupervised classification in the context of cluster analysis?

A) Using a decision tree for data classification
B) Assigning predefined labels to data points
C) Grouping similar data points together without predefined labels
D) Creating a scatter plot of data points

3. How can you interpret the impurity measures in an icicle plot of a decision tree?

A) Lower impurity implies more homogeneity within a leaf node.
B) Impurity measures are irrelevant in decision tree analysis.
C) Impurity measures represent the number of data points in a leaf node.
D) Higher impurity indicates better separation of classes.

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

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

5. What are variable selection methods for decision trees used to determine the most important features?

A) Principal Component Analysis (PCA)
B) F-test for feature significance
C) Recursive feature elimination
D) Information gain or Gini impurity reduction

Solutions: