Here 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:

**01. What is a linear Perceptron?**

**a)**A linear Perceptron is a general linear model.

**b)**A linear Perceptron is a generalized linear model.

**c)**A linear Perceptron is a non-parametric model.

**d)**A linear Perceptron is a nonlinear model.

**02. 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?**

**a)**19

**b)**21

**c)**22

**d)**25

**03. Refer to the fit summary from SAS Visual Statistics in the exhibit below.**

**What can be concluded from the fit summary?**

**a)**Customer Value Level is not a significant predictor in this model.

**b)**Customer Value Level C has no important variables associated with it.

**c)**Average Sales is a significant predictor when Customer Value Level = E.

**d)**Average Sales is an important predictor when Customer Value Level = C.

**04. 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?**

**a)**The sample means from the validation data set are applied to the training and test data sets.

**b)**The sample means from the training data set are applied to the validation and test data sets.

**c)**The sample means from the test data set are applied to the training and validation data sets.

**d)**The sample means from each partition of the data are applied to their own partition.

**05. Which software does the SAS Enterprise Miner Open Source Integration node use to execute R programs?**

**a)**SAS/IML

**b)**SAS/STAT

**c)**SAS/ACCESS

**d)**SAS/OR

**06. Refer to the Eigenvalue plot from SAS Enterprise Miner shown below.**

**According to the Kaiser-Guttman method, how many principal components should be retained?**

**a)**6

**b)**4

**c)**10

**d)**1

**07. Which statement is true for negative binomial and Poisson regression models?**

**a)**Poisson regression models are used for count data, and negative binomial models are used for binary responses.

**b)**The canonical link function for Poisson regression is the log, while for negative binomial it is the logit.

**c)**Negative binomial models accommodate negative integers while Poisson regression does not.

**d)**Poisson regression is a special case of negative binomial regression.

**08. A predictive model uses a data set that has several variables with missing values. What two problems can arise with this model?**

**a)**The model will likely be overfit.

**b)**There will be a high rate of collinearity among input variables.

**c)**Fewer observations will be used in the model building process.

**d)**New cases with missing values on input variables cannot be scored without extra data processing.

**09. Refer to the exhibit:**

**For the ROC curve shown, what is the meaning of the area under the curve?**

**a)**percent concordant plus percent tied

**b)**percent concordant plus (.5 * percent tied)

**c)**percent concordant plus (.5 * percent discordant)

**d)**percent discordant plus percent tied

**10. What is the maximum number of response variables that SAS Visual Statistics allows for a decision tree?**

**a)**1

**b)**2

**c)**3

**d)**4

## Answers:

Question: 1 | Answer: b | Question: 2 | Answer: c |

Question: 3 | Answer: c | Question: 4 | Answer: b |

Question: 5 | Answer: a | Question: 6 | Answer: b |

Question: 7 | Answer: d | Question: 8 | Answer: c, d |

Question: 9 | Answer: b | Question: 10 | Answer: a |

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