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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: SAS Visual Statistics Cross-functional Tasks | 22% | - Perform model validation - Use interactive group-by functionality - Filter data used for a model - Prepare data using SAS Visual Analytics |
| Topic 2: Building and Assessing Regression-type Models | 41% | - Perform linear regression modeling - Assess model fit and diagnostics - Perform generalized additive modeling - Explain concepts of linear models - Perform nonparametric logistic regression modeling - Perform generalized linear regression modeling |
| Topic 3: Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| Topic 4: Building and Assessing Segmentation Models | 28% | - Perform unsupervised segmentation using cluster analysis - Perform supervised segmentation using decision trees - Assess and interpret decision tree performance - Analyze and interpret cluster results |
Question 1
When building a Generalized Linear Model in SAS Visual Statistics, which link function is available?
A. Poisson
B. Negative Binomial
C. Log
D. Gaussian
Question 2
When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?
A. Poisson distribution with a log link function
B. Normal distribution with an identity link function
C. Exponential distribution with a square root link function
D. Binomial distribution with a logit link function
Question 3
Which SAS tools can be used to score new data using score code generated by SAS Visual Statistics?
A. SAS Enterprise Miner
B. SAS Data Integration Studio
C. SAS Studio
D. SAS Enterprise Guide
Question 4
Which statement is true regarding the number of polylines created in a Parallel Coordinates plot during Cluster Analysis?
A. It is calculated using the number of variables visible in the plot.
B. It cannot exceed 3,000.
C. It is calculated using the variable with the greatest number of bins.
D. It is calculated using the number of variables used in the cluster analysis.
Question 5
What conditions might make models less comparable in SAS Visual Statistics?
A. If they have different learning rates
B. If they use the same dataset and response variable
C. If they have similar AUC values
D. If they are both logistic regression models
Solutions:
| Question 1 Answer: C | Question 2 Answer: D | Question 3 Answer: A,B,C,D | Question 4 Answer: A | Question 5 Answer: A,C |
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