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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building Predictive Models | 40% | - Regression models - Decision trees - Neural networks - Gradient boosting |
| Model Assessment and Selection | 20% | - Model fit statistics - Model comparison - ROC and Lift curves |
| Scoring and Deployment | 20% | - Model deployment - Model scoring |
| Data Preparation and Exploration | 20% | - Data quality - Data exploration using SAS Visual Statistics - Importing data |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. Interactive group-by analysis can be performed for each of the following in Visual Statistics except:
A) Logistic regression
B) Generalized linear model
C) Decision tree
D) Linear regression
2. Which of the following tasks in SAS Visual Analytics involves reducing the granularity of categorical data?
A) Imputing a variable
B) Creating a dummy variable
C) Aggregating a measure
D) Transforming a variable
3. What information can you gather from Leaf statistics in a decision tree analysis?
A) The distribution of target variable values in each leaf node
B) The tree's decision rules for each leaf node
C) The total number of data points in each leaf node
D) The tree's overall accuracy and error rate
4. 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) 
5. In SAS Visual Statistics, which role is typically assigned to variables in cluster analysis?
A) Input
B) Output
C) Predictor
D) Target
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: A,C | Question # 4 Answer: C | Question # 5 Answer: A |








