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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. How can score code be implemented to score new data using SAS Enterprise Miner?

A) By creating a scoring node in a SAS Enterprise Miner process flow
B) By manually executing the code in a command-line interface
C) By pasting the code into a web browser
D) By importing the code into SAS Data Integration Studio

2. What is the primary purpose of reviewing the residual plot in linear regression analysis?

A) To assess the linearity assumption and identify potential issues
B) To detect outliers in the predictor variables
C) To determine the p-value associated with the response variable
D) To calculate the coefficient of determination (R-squared)

3. You perform a logistic regression on a multinomial response variable in SAS Visual Statistics that has 3 levels: Small, Medium, Large. "Large" is specified as the event.
Which statement is true?

A) An ordinal logistic regression is performed.
B) A multinomial logistic regression is performed.
C) The other levels are offset to account for exposure.
D) The other levels are grouped into one non-event.

4. In SAS Visual Analytics, which of the following tasks involves converting a categorical variable into a numerical one?

A) Transforming a variable
B) Replacing dirty data
C) Creating a dummy variable
D) Aggregating a measure

5. When interpreting comparison results using the Assessment panel, what information can be obtained?

A) The distribution of predictor variables
B) The number of iterations performed by each model
C) The relationship between two predictor variables
D) Model performance metrics, such as AUC and KS Statistic

Solutions: