Here are the sample questions which will help you be familiar with SAS Text Analytics, Time Series, Experimentation and Optimization (A00-226) 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 A00-226 Sample Questions:
Q 1: After creating a data source within the SAS Code node, which macro is used to modify the metadata of the data source (specifically changing the roles and levels for each variable)?
Q 2: In the Text Topic node, the Singular Value Decomposition (SVD) dimensions are rotated. What is the purpose of this rotation?
A: To interpret each dimension with a set of terms.
B: To ensure the topics are relevant to your interests.
C: To determine the number of topics that are discovered.
D: To avoid producing topics that are too similar
Q 3: Refer to the exhibit below from an Incremental Response node from SAS Enterprise Miner.
What can be inferred from the properties above?
A: The input data set contains an expected revenue variable, with values for individual customers.
B: The expected revenue for individual customers is $9.50.
C: The expected revenue for individual customers is $10.
D: The expected revenue for individual customers is the estimated outcome from the model.
Q 4: What distinguishes a deterministic linear trend from other local linear trends?
A: A deterministic linear trend is always linear; other local linear trends are only linear over certain intervals.
B: A deterministic linear trend does not contain a seasonal component; other local linear trends do contain a seasonal component.
C: A deterministic linear trend shows the same slope at all time periods; other local linear trends do not show the same slope at all time periods.
D: A deterministic trend has a predetermined slope; other local linear trends do not have a pre-determined slope.
Q 5: What is a primary value of text mining as applied to forensic linguistics analysis?
A: Determining the native language of a suspect can help identify where a suspect may reside.
B: The usage of certain emotion-based nouns, verbs, and adjectives indicate criminal pathology.
C: Word frequencies of written or spoken communication can help discriminate between suspects.
D: Determines if the written or spoken communication is the subject's second language.
Q 6: What is an example of time series forecasting?
A: A fire department wants to know how many fires it will likely need to fight during the holidays, so that it can staff accordingly.
B: A dried fruit company sends out marketing postcards and models who will respond.
C: A hospital wants to know how long its patients will survive after open heart surgery so that adverse effects can be caught early.
D: A glue manufacturer wants to know how long it will take for its glue to dry.
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