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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Refer to the exhibit from SAS Visual Statistics:

What can be concluded from the lift plot shown in the exhibit?

A) The response rate for the best 20% is predicted to increase 5 times under the fitted model.
B) The 20% of cases with the highest predicted probability of the modeled event level is expected to capture 2.75 times as many events as a random sample of the same size.
C) The response rate for the best 20% is predicted to be 2.75 times greater than the sample fitted in the model.
D) The 20% of cases with the lowest predicted probability of the modeled event level is predicted to capture 2.75 times as many events as a random sample of 20%.

2. Given a scenario where the response variable represents the number of accidents in a day, what distribution and link function might be appropriate for modeling?

A) Exponential distribution with a square root link function
B) Normal distribution with an identity link function
C) Poisson distribution with a log link function
D) Logistic distribution with a logit link function

3. What does it mean to prune a decision tree?

A) To trim branches of the tree to reduce complexity and overfitting
B) To increase the depth of the tree to improve accuracy
C) To remove all leaf nodes and keep only the root node
D) To convert the decision tree into a random forest model

4. When performing a logistic regression in SAS Visual Statistics, the default prediction cutoff is .50. If you increase the cutoff to .80 then derive predicted values, which statement is the expected outcome?

A) The predicted events remain unchanged and the predicted probabilities increase.
B) The predicted events decrease and the predicted probabilities remain unchanged.
C) The predicted events remain unchanged and the predicted probabilities decrease.
D) The predicted events increase and the predicted probabilities remain unchanged.

5. What does a Lift chart evaluate in terms of model performance?

A) The interaction effects between predictor variables
B) The correlation between predictor variables
C) The distribution of the response variable
D) The relative performance of the model compared to a random model

Solutions: