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SASInstitute A00-485 Exam Syllabus Topics:

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. In the context of assessing model results, what information can be interpreted from the Fit Summary window?

A) The distribution of the response variable in the dataset
B) A summary of the model's goodness of fit and performance metrics
C) A detailed description of the data preprocessing steps
D) A list of all predictor variables used in the model

2. Refer to the following exhibit:

After creating a decision tree in SAS Visual Statistics, what is the value in deriving a Leaf ID Variable?

A) Use the leaf ID to identify clusters.
B) Use the leaf ID data item in filters in other types of visualizations.
C) Use the leaf ID to identify the most important variables.
D) Use the leaf ID to rank order by posterior probabilities.

3. Interactions can be created and added to a linear regression model.
Which statement is true about interactions?

A) Measures and categories can be combined to create an interaction.
B) Each interaction is limited to 3 effects or fewer.
C) The maximum number of interactions allowed in a model is 3.
D) An interaction can be created for a squared category variable.

4. When performing decision tree analysis in SAS Visual Statistics, how does the property setting for
"include missing" modify the usage of missing values within categorical discrete predictors?

A) assigns its own level
B) imputes the median of the predictor's known values
C) imputes the mean of the predictor's known values
D) assigns the smallest available machine value

5. Refer to the exhibit:

Based on the Validation Data in the Model Comparison output which conclusions are valid? (Choose two.)

A) Decision Tree model would be selected at lift=5
B) Decision Tree model would be selected at lift=20
C) Logistic Regression model would be selected at lift=5
D) Logistic Regression model would be selected at lift=20

Solutions: