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SASInstitute A00-485 Exam Syllabus Topics:

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What are decision tree properties that can be defined during model construction?

A) The maximum depth of the tree
B) The number of neighbors in a k-nearest neighbors model
C) The learning rate for gradient boosting
D) The minimum number of data points in a leaf node

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

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

3. How is a multinomial response variable used in SAS Visual Statistics when building a logistic regression model?

A) It is used to define the outcome categories.
B) It is used as an event variable.
C) It is used as a predictor variable.
D) It is not used in logistic regression modeling.

4. What is the purpose of implementing score code generated by SAS Visual Statistics?

A) To calculate the p-values of predictor variables
B) To assess the distribution of residuals in the model
C) To apply the trained model to new data for predictions
D) To evaluate the performance of the scoring code

5. Select the best distribution to model with linear regression.

A)

B)

C)

D)

Solutions: