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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building and Assessing Regression-type Models | 41% | - Perform generalized linear regression modeling - Perform linear regression modeling - Perform nonparametric logistic regression modeling - Assess model fit and diagnostics - Explain concepts of linear models - Perform generalized additive modeling |
| SAS Visual Statistics Cross-functional Tasks | 22% | - Perform model validation - Use interactive group-by functionality - Prepare data using SAS Visual Analytics - Filter data used for a model |
| Building and Assessing Segmentation Models | 28% | - Perform supervised segmentation using decision trees - Perform unsupervised segmentation using cluster analysis - Assess and interpret decision tree performance - Analyze and interpret cluster results |
| Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. Refer to the following exhibit:
After creating a decision tree in SAS Visual Statistics, what is the value in deriving a Leaf ID Variable?
A) Use the leaf ID to identify the most important variables.
B) Use the leaf ID to rank order by posterior probabilities.
C) Use the leaf ID to identify clusters.
D) Use the leaf ID data item in filters in other types of visualizations.
2. What conditions might make models less comparable in SAS Visual Statistics?
A) If they have similar AUC values
B) If they are both logistic regression models
C) If they have different learning rates
D) If they use the same dataset and response variable
3. Refer to the exhibit:
An economist is predicting demand using a linear regression model.
If all of the effect variables equal 1, what is the predicted demand?
A) 362.415133
B) 352.415433
C) 352.405432
D) 352.454433
4. Refer to the exhibit:
Based on the Validation Data in the Model Comparison output which conclusions are valid? (Choose two.)
A) Decision Tree model would be selected at lift=5
B) Logistic Regression model would be selected at lift=20
C) Decision Tree model would be selected at lift=20
D) Logistic Regression model would be selected at lift=5
5. In linear regression, what does the coefficient of determination (R-squared) measure?
A) The p-value associated with the intercept term
B) The degree of multicollinearity among predictors
C) The impact of outliers on the model
D) The goodness of fit of the model to the data
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A,C | Question # 3 Answer: B | Question # 4 Answer: C,D | Question # 5 Answer: D |


