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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

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

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

2. 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 tree's training and validation performance metrics
C) The feature importance for each variable in the tree
D) The decision boundaries between leaf nodes

3. Explain what an icicle plot represents in decision tree analysis.

A) It shows the feature importance for each variable in the tree.
B) It summarizes the performance metrics of the decision tree.
C) It visualizes the distribution of data points in each leaf node.
D) It displays the hierarchical structure of the decision tree.

4. What is the primary goal of linear models in statistical modeling?

A) To capture non-linear relationships in data
B) To establish a linear relationship between variables
C) To predict categorical outcomes
D) To classify data into distinct groups

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

Solutions: