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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Preparation and Exploration in SAS Viya | - Exploratory data analysis and visualization - Loading and preparing data for Visual Statistics |
| Topic 2: Predictive Modeling Fundamentals | - Regression modeling concepts
|
| Topic 3: Machine Learning Methods in Visual Statistics | - Clustering techniques - Decision trees and random forests concepts |
| Topic 4: Model Evaluation and Interpretation | - Interpreting model outputs and reports - Assessing model performance |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. How is the KS Statistic typically used when interpreting an ROC chart?
A) To measure the area under the ROC curve
B) To assess the balance between sensitivity and specificity
C) To identify the optimal prediction cut-off threshold
D) To evaluate the overall performance of a classification model
2. What are the roles that can be assigned in a generalized linear model (GLM)?
A) Offset
B) Target
C) Intercept
D) Predictor
3. What is the purpose of implementing score code generated by SAS Visual Statistics?
A) To apply the trained model to new data for predictions
B) To assess the distribution of residuals in the model
C) To calculate the p-values of predictor variables
D) To evaluate the performance of the scoring code
4. What does a ROC chart help assess in model comparison?
A) The stability of model predictions
B) The distribution of residuals in the models
C) The trade-off between true positives and false positives at different thresholds
D) The correlation between predictor variables
5. When building a cluster analysis in SAS Visual Statistics, which of the following algorithms is commonly used for partitioning data into clusters?
A) Decision Tree
B) K-means
C) Linear Regression
D) Principal Component Analysis (PCA)
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A,B,D | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: B |
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