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| Section | Objectives |
|---|---|
| Model Diagnostics and Validation | - Influence and leverage - Goodness-of-fit measures |
| ANOVA and General Linear Models | - One-way and multi-way ANOVA - GLM procedures in SAS |
| Logistic Regression | - Binary logistic regression - Model fit and diagnostics |
| Multiple Regression | - Interaction effects - Model building and selection - Multicollinearity diagnostics |
| Simple Linear Regression | - Residual analysis - Model assumptions and interpretation - Estimation and inference |
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NEW QUESTION # 28
Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4).
Answer: A
NEW QUESTION # 29
Refer to the exhibit:
An analyst examined logistic regression models for predicting whether a customer would make a
purchase. The ROC curve displayed summarizes the models. Using the selected model and the analyst's
decision rule, 25% of the customers who did not make a purchase are incorrectly classified as purchasers.
What can be concluded from the graph?
Answer: B
NEW QUESTION # 30
The total modeling data has been split into training, validation, and test data. What is the best data to use for model assessment?
Answer: B
NEW QUESTION # 31
A financial services manager wants to assess the probability that certain clients will default on their Home Equity Line of Credit (HELOC). A former employee left the code listed below.
The training data set is named HELOC, while a similar data set of more recent clients is named RECENT_HELOC.
Which SAS data steps will calculate the predicted probability of default on recent clients? (Choose two.)
Answer: A,D
NEW QUESTION # 32
This question will ask you to provide missing code segments.
A logistic regression model was fit on a data set where 40% of the outcomes were events (TARGET=1) and
60% were non-events (TARGET=0). The analyst knows that the population where the model will be deployed has 5% events and 95% non-events. The analyst also knows that the company's profit margin for correctly targeted events is nine times higher than the company's loss for incorrectly targeted non-event.
Given the following SAS program:
What X and Y values should be added to the program to correctly score the data?
Answer: A
NEW QUESTION # 33
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