SAS Advanced Analytics Professional (A00-225) Certification Exam Sample Questions

A00-225 Dumps Free, A00-225 PDF Download, SAS Advanced Analytics Professional Dumps Free, SAS Advanced Analytics Professional PDF Download, A00-225 Free DownloadHere are the sample questions which will help you be familiar with SAS Advanced Predictive Modeling (A00-225) exam style and structure. We encourage you to try our Demo SAS Advanced Analytics Professional Certification Practice Exam to measure your understanding of exam structure in an environment which simulates the SAS Certified Advanced Analytics Professional Using SAS 9 Certification test environment.

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SAS A00-225 Sample Questions:

Q 1: What is the maximum number of response variables that SAS Visual Statistics allows for a decision tree?
Options:
A: 2
B: 4
C: 1
D: 3
 
Q 2: When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for handling the mean imputation?
Options:
A: The sample means from the training data set are applied to the validation and test data sets.
B: The sample means from the validation data set are applied to the training and test data sets.
C: The sample means from each partition of the data are applied to their own partition.
D: The sample means from the test data set are applied to the training and validation data sets.
 
Q 3: What is a linear Perceptron?
Options:
A: A linear Perceptron is a non-parametric model.
B: A linear Perceptron is a nonlinear model.
C: A linear Perceptron is a general linear model.
D: A linear Perceptron is a generalized linear model.
 
Q 4: A predictive model uses a data set that has several variables with missing values. What two problems can arise with this model? (Choose two.)
Options:
A: The model will likely be overfit.
B: There will be a high rate of collinearity among input variables.
C: New cases with missing values on input variables cannot be scored without extra data processing.
D: Fewer observations will be used in the model building process.
 
Q 5: Consider a Generalized Additive Neural Network (GANN) with 3 continuous inputs and 2 hidden nodes for each input. How many parameters do you need to estimate when training the neural network?
Options:
A: 19
B: 21
C: 25
D: 22
 
Q 6: Refer to the fit summary from SAS Visual Statistics in the exhibit below.

What can be concluded from the fit summary?
Options:
A: Average Sales is a significant predictor when Customer Value Level = E.
B: Customer Value Level C has no important variables associated with it.
C: Average Sales is an important predictor when Customer Value Level = C.
D: Customer Value Level is not a significant predictor in this model.

Answers:

Question: 1 Answer: C Question: 2 Answer: A
Question: 3 Answer: D Question: 4 Answer: C, D
Question: 5 Answer: D Question: 6 Answer: A

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