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SASInstitute A00-485 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Preparation and Exploration20%- Data quality
- Importing data
- Data exploration using SAS Visual Statistics
Topic 2: Model Assessment and Selection20%- Model fit statistics
- Model comparison
- ROC and Lift curves
Topic 3: Scoring and Deployment20%- Model scoring
- Model deployment
Topic 4: Building Predictive Models40%- Neural networks
- Decision trees
- Regression models
- Gradient boosting

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

Question 1

Which SAS tool is suitable for creating complex data manipulation and transformation workflows in a visual interface?

A. SAS Visual Analytics
B. SAS Enterprise Guide
C. SAS Studio
D. SAS Visual Data Builder


Question 2

Which statement is true about performing regressions in SAS Visual Statistics?

A. You can build both a linear regression or a logistic regression with a generalized linear model.
B. You can specify an ordinal classifier as the response variable with linear regression.
C. You can specify a multinomial classifier as the response variable with linear regression.
D. You can build neither a linear regression nor a logistic regression with a generalized linear model.


Question 3

Which statement is true about Decision Trees in SAS Visual Statistics

A. Decision trees cannot handle continuous dependent variables.
B. Decision trees cannot handle missing values.
C. Decision trees can be used for classification and estimation.
D. Decision trees can be used for outlier detection.


Question 4

You would like to see the minimum and maximum values for all of your measures so that you can filter variables as needed.
Which is the most efficient way to do that?

A. Create aggregated measures using the Min and Max aggregations.
B. Create a calculated item subtracting the Min aggregation from the Max aggregation.
C. Select a histogram object for each measure.
D. Select View Measure Details within the Actions menu to the right of the dataset name.


Question 5

What is the purpose of deriving a cluster ID variable in cluster analysis?

A. To create a scatter plot of data points
B. To assign cluster labels to data points
C. To calculate the distance between clusters
D. To set parallel coordinate properties


Solutions:

Question 1
Answer: D
Question 2
Answer: A
Question 3
Answer: C
Question 4
Answer: D
Question 5
Answer: B

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