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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. When assessing the quality of a linear regression model, what does a low p-value associated with the F-statistic suggest?

A) The model has a weak linear relationship with the response.
B) The model has a high level of multicollinearity.
C) The model is a poor fit for the data.
D) The model has a significant overall explanatory power.

2. What properties can be defined in a logistic regression model?

A) The learning rate
B) Coefficients and p-values
C) The distribution of the response variable
D) The number of iterations

3. When investigating leaf nodes in a decision tree, what does it reveal about the data?

A) The class labels assigned to each leaf node
B) The statistical significance of each leaf node
C) The decision rules leading to each leaf node
D) The feature values associated with each leaf node

4. 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 be 2.75 times greater than the sample fitted in the model.
B) 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%.
C) The response rate for the best 20% is predicted to increase 5 times under the fitted model.
D) 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.

5. Refer to the exhibit from a linear regression model in SAS Visual Statistics:

Based on the table above and assuming a significance level of 0.05, what can be concluded about the linear regression model?

A) For one one-unit increase in Average Sales, there is an expected increase in the response of
4475.443.
B) The Intercept is an important predictor of the response.
C) For a 1371.5 unit decrease in Total Promos, there is an expected one-unit increase in the response.
D) Age is a significant predictor of the response.

Solutions: