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SAS A00-255 Exam Summary:-
- Name of the Exam: SAS Predictive Modeling Using SAS Enterprise Miner 14
- Exam Code: A00-255
- Exam Price: $250 (USD)
- Duration: 165 minutes
- Number of Questions: 55-60
- Passing Score: 725/1000
SAS A00-255 Exam Topics:-
- Data Sources – 20-25%
- Building Predictive Models – 35-40%
- Predictive Model Assessment and Implementation – 25-30%
- Pattern Analysis – 10-15%
Improve Your Knowledge-Base:
Get access to some of the sample A00-255 practice test questions to boost your knowledge base. Preparation is a steady process for some time, and you must always try to keep improving via learning. Access the questions from anywhere and from any device. The easy access to the questions would help you to get better with the A00-255 exam topics. You can solve these questions easily or learn new things from them.
Here Are Some Useful Questions:
01. Which of the following solves problems for you when you impute missing values?
a) When you impute a synthetic value, it replaces missing values with 1 or 0.
b) When you impute a synthetic value, it eliminates the incomplete case problem.
c) When you impute a synthetic value, predictive information is retained.
d) When you impute a synthetic value, each missing value becomes an input to the model.
Answer: b
02. Which of the following is not true about results produced by the Regression node?
a) Model Information provides you with information that includes the number of target categories and the number of model parameters.
b) Variable Summary information identifies the roles of variables used by the Regression node.
c) Type 3 Analysis of Effects provides you with information about the number of parameters that each input contributes to the model.
d) Fit Statistics can provide information that affects decision predictions, but does not affect estimate predictions.
Answer: d
03. Which of the following is not a good reason to”regularize” input distributions using a simple transformation?
a) Another benefit is ease in model interpretation.
b) One benefit is improved model performance.
c) When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
d) Regression models are sensitive to extreme or outlying values in the input space.
Answer: a
04. Which of the following sequential selection methods do you use so that SAS Enterprise Miner will look at all variables already included in the model and delete any variable that is not significant at the specified level?
a) Backward
b) Forward
c) Stepwise
d) None
Answer: d
05. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
The variable Branch has how many levels?
a) 8
b) 12
c) 19
d) 47
Answer: c
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