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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. After a logistic regression has been created in SAS Visual Statistics, you discover that not all observations were used to create the model.
How would you run the model on all of the data?

A) Include the correct offset term.
B) Include the correct interaction term.
C) Select Use Variable Selection on the properties tab.
D) Select Informative Missingness on the properties tab.

2. Refer to the exhibit:

What does the Residual Plot from a linear regression model reveal?

A) It suggests the error variance is constant.
B) The model is not capturing all of the available signals in the data.
C) It suggests the errors are uncorrelated.
D) There is an approximately equal number of positive and negative residuals.

3. What information can you gather from Leaf statistics in a decision tree analysis?

A) The total number of data points in each leaf node
B) The tree's decision rules for each leaf node
C) The tree's overall accuracy and error rate
D) The distribution of target variable values in each leaf node

4. What does it mean to create dummy variables in SAS Visual Data Builder?

A) Generating artificial data points
B) Converting categorical variables into binary variables
C) Replacing missing values with zeros
D) Aggregating multiple measures into one variable

5. When should you replace dirty data with missing values in SAS Visual Analytics?

A) When the data is incorrect or invalid
B) When the data contains outliers
C) When you want to remove missing values
D) When you want to create a new variable

Solutions: