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SASInstitute A00-485 Exam Syllabus Topics:

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What can be interpreted from the Summary Table for model comparison, including statistics and variable importance?

A) The distribution of predictor variables
B) The correlation matrix of predictor variables
C) The number of iterations performed by each model
D) Model performance metrics and their relative importance

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

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

3. The Leaf size property within a decision tree is changed from 5 to 10 and no other stopping rules were met.
How will the tree change?

A) The tree will train more slowly.
B) The tree will be simpler.
C) The tree will be harder to interpret.
D) The tree will be more complex.

4. How can you appropriately change the number of clusters in a k-means cluster analysis?

A) By increasing the number of iterations
B) By changing the K-value
C) By adjusting the learning rate
D) By modifying the random seed

5. Refer to the fit summary from in the exhibit below.

What can be concluded from the fit summary?

A) Debt to income ratio is a significant predictor when Job Type = Sales.
B) Debt to income ratio is a significant predictor when Job Type = Mgr.
C) Job Type = Office has no important variables associated with it.
D) Job Type is not a significant predictor in this model.

Solutions: