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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Cluster Analysis in SAS Visual Statistics is categorized as which type of machine learning?

A) Supervised learning
B) Reinforcement learning
C) Unsupervised learning
D) Semi-supervised learning

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

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

3. What is the primary benefit of exporting score code for model deployment?

A) It provides insights into the distribution of predictor variables.
B) It allows for model performance assessment on a test dataset.
C) It enables scoring of new data without the need for SAS Visual Statistics.
D) It automatically generates new predictor variables.

4. What does a ROC chart help assess in model comparison?

A) The trade-off between true positives and false positives at different thresholds
B) The correlation between predictor variables
C) The stability of model predictions
D) The distribution of residuals in the models

5. What is the primary purpose of scoring functionality in SAS Visual Statistics?

A) To evaluate model performance on a test dataset
B) To select the best model for a given dataset
C) To assess the distribution of predictor variables
D) To generate code for deploying models in production

Solutions: