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SASInstitute A00-255 Exam Syllabus Topics:

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

1. 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?
Response:

A) Stepwise
B) None
C) Backward
D) Forward

2. Multicollinearity in regression refers to which of the following?
Response:

A) non-normality of the target variable
B) high skewness in distributions of input variables
C) high correlations among input variables
D) non-constant variance of the target variable

3. Which of the following solves problems for you when you impute missing values?
Response:

A) When you impute a synthetic value, each missing value becomes an input to the model.
B) When you impute a synthetic value, predictive information is retained.
C) When you impute a synthetic value, it eliminates the incomplete case problem.
D) When you impute a synthetic value, it replaces missing values with 1 or 0.

4. If we were to add a Transformation node, what would be the default transformation for interval inputs for the present scenario?
Response:

A) Maximum Correlation
B) none of the above
C) Maximum Normal
D) Optimal

5. The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:

A) none of the above
B) the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron
C) the average of the absolute values of parameter estimates between the input and all of the hidden neurons
D) the highest absolute value of the parameter estimate between the input and any of the hidden neurons

Solutions: