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It is a lifetime study time. The society advocates us to further our study and improve working skills at every aspect. For exam candidates like you it is of great importance to pass the SASInstitute exams effectively. That is why we offer you the excellent A00-485 learning materials: Modeling Using SAS Visual Statistics compiled by professional experts. Now, let us take a comprehensive look of the features of the A00-485 actual lab questions as follow:
SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and Assessing Segmentation Models | 28% | - Analyze and interpret cluster results - Perform unsupervised segmentation using cluster analysis - Assess and interpret decision tree performance - Perform supervised segmentation using decision trees |
| Topic 2: SAS Visual Statistics Cross-functional Tasks | 22% | - Use interactive group-by functionality - Prepare data using SAS Visual Analytics - Filter data used for a model - Perform model validation |
| Topic 3: Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| Topic 4: Building and Assessing Regression-type Models | 41% | - Perform linear regression modeling - Assess model fit and diagnostics - Perform generalized additive modeling - Perform nonparametric logistic regression modeling - Explain concepts of linear models - Perform generalized linear regression modeling |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. You would like to build a cluster analysis using several variables related to demographics. You noticed that the variable Inferred HH Education is a nominal variable with values of "High School Grad",
"College Grad", etc.
Which action allows you to incorporate this variable in the cluster analysis without returning a warning?
A) 
B) 
C) 
D) 
2. What are variable selection methods for decision trees used to determine the most important features?
A) Information gain or Gini impurity reduction
B) Principal Component Analysis (PCA)
C) F-test for feature significance
D) Recursive feature elimination
3. When specifying Cluster Roles for Cluster Analysis in SAS Visual Statistics, which condition is correct?
A) At least two variables are required.
B) A target variable is required.
C) Interaction items are allowed.
D) Category items are not allowed.
4. Assuming the event level is the same for both models, which pair of models can be compared?
A) 
B) 
C) 
D) 
5. What does the Variable Importance feature help with when choosing the best fitting group-by model?
A) Identifying the most influential predictors
B) Assessing the significance of each predictor
C) Evaluating the multicollinearity among predictors
D) Understanding the distribution of the target variable
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: A |
