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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| Topic 2: Building and Assessing Regression-type Models | 41% | - Explain concepts of linear models - Perform nonparametric logistic regression modeling - Perform generalized linear regression modeling - Assess model fit and diagnostics - Perform linear regression modeling - Perform generalized additive modeling |
| Topic 3: SAS Visual Statistics Cross-functional Tasks | 22% | - Filter data used for a model - Perform model validation - Use interactive group-by functionality - Prepare data using SAS Visual Analytics |
| Topic 4: Building and Assessing Segmentation Models | 28% | - Perform unsupervised segmentation using cluster analysis - Analyze and interpret cluster results - Perform supervised segmentation using decision trees - Assess and interpret decision tree performance |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
Question 1
You would like to see the minimum and maximum values for all of your measures so that you can filter variables as needed.
Which is the most efficient way to do that?
A. Select a histogram object for each measure.
B. Create a calculated item subtracting the Min aggregation from the Max aggregation.
C. Select View Measure Details within the Actions menu to the right of the dataset name.
D. Create aggregated measures using the Min and Max aggregations.
Question 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 used to define the outcome categories.
C. It is used as an event variable.
D. It is not used in logistic regression modeling.
Question 3
Given a scenario where the response variable represents the time until an event occurs, what distribution and link function might be appropriate for modeling?
A. Poisson distribution with a log link function
B. Logistic distribution with a logit link function
C. Normal distribution with an identity link function
D. Exponential distribution with a log link function
Question 4
What information can you gather from Leaf statistics in a decision tree analysis?
A. The total number of data points in each leaf node
B. The tree's overall accuracy and error rate
C. The tree's decision rules for each leaf node
D. The distribution of target variable values in each leaf node
Question 5
Refer to the exhibit:
Which is the modeling approach that should be used when fitting the Target Gift Amount variable?
A. Generalized linear model with a Normal distribution and Log Link.
B. Linear regression model with Interaction effects.
C. Logistic regression model.
D. Generalized linear model with a Poisson distribution and Identity link.
Solutions:
| Question 1 Answer: C | Question 2 Answer: B | Question 3 Answer: D | Question 4 Answer: A,D | Question 5 Answer: A |




