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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building Predictive Models | 40% | - Gradient boosting - Regression models - Neural networks - Decision trees |
| Topic 2: Data Preparation and Exploration | 20% | - Importing data - Data exploration using SAS Visual Statistics - Data quality |
| Topic 3: Scoring and Deployment | 20% | - Model scoring - Model deployment |
| Topic 4: Model Assessment and Selection | 20% | - ROC and Lift curves - Model comparison - Model fit statistics |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. What properties can be assigned when comparing models in SAS Visual Statistics?
A) The learning rate for gradient boosting models
B) The color scheme for visualization
C) The variables to include in the model comparison
D) The number of observations in the dataset
2. In a generalized linear model, what is the role of the link function in transforming the linear predictor?
A) It determines the distribution of the response variable.
B) It maps the linear predictor to the range of the response variable.
C) It ensures that the linear predictor is always positive.
D) It scales the predictor variables.
3. What is the primary purpose of specifying the link function in logistic regression?
A) To determine the distribution of the response variable
B) To ensure that all predictor variables are used
C) To control the significance level of predictor variables
D) To establish the relationship between the linear predictor and the probability of an event
4. When performing a logistic regression in SAS Visual Statistics, the default prediction cutoff is .50. If you increase the cutoff to .80 then derive predicted values, which statement is the expected outcome?
A) The predicted events remain unchanged and the predicted probabilities decrease.
B) The predicted events increase and the predicted probabilities remain unchanged.
C) The predicted events decrease and the predicted probabilities remain unchanged.
D) The predicted events remain unchanged and the predicted probabilities increase.
5. When interpreting comparison results using the Assessment panel, what information can be obtained?
A) The number of iterations performed by each model
B) Model performance metrics, such as AUC and KS Statistic
C) The distribution of predictor variables
D) The relationship between two predictor variables
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: B |
