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SASInstitute A00-255 Exam Overview:

Certification Vendor:SASInstitute
Exam Name:SAS Predictive Modeling Using SAS Enterprise Miner 14
Exam Number:A00-255
Available Languages:English
Exam Price:$250 USD
Real Exam Qty:55–60
Certificate Validity Period:Valid indefinitely once earned
Related Certifications:SAS Certified Advanced Analytics Professional
Passing Score:725 (scale 200–1000)
Exam Format:Short answer, Multiple choice, Performance-based
Exam Duration:165 minutes
Recommended Training:SAS Enterprise Miner Training Courses
Exam Registration:Pearson VUE Registration
SAS Certification Registration
Sample Questions:SASInstitute A00-255 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:Recommended: experience with SAS Enterprise Miner, data mining and predictive modeling concepts; no mandatory prerequisites
Official Syllabus URL:https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler-14.html

SASInstitute A00-255 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Predictive Model Assessment and Implementation25–30%- Evaluate performance via profit/loss and comparison
- Adjust for oversampling and sampling methods
- Score and deploy models
- Apply appropriate fit statistics
Topic 2: Pattern Analysis10–15%- Interpret pattern discovery results
- Identify clusters and segments
Topic 3: Data Sources20–25%- Modify and prepare source data for modeling
- Explore and assess data sources
- Create data sources from SAS tables
Topic 4: Building Predictive Models35–40%- Build models using decision trees
- Build models using neural networks
- Understand predictive modeling concepts
- Build models using regression techniques

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

Question #1

What percentage of observations in the test data has TARGET=1?
Response:

  • A. 16.8874
  • B. 16.5924
  • C. 83.3333
  • D. 16.6627
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #2

Perform these tasks in SAS Enterprise Miner:
Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

Run the Decision Tree node.
Suppose that the data has been oversampled and the probability that TARGET=1 is 0.10 in the population. Incorporate the above scenario and run the Decision Tree node again.
What is the misclassification rate in the validation data set?
Response:

  • A. 0.10
  • B. 0.162252
  • C. 0.157016
  • D. 0.154788
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Question #3

You are building a model for a marketing campaign. Every responder to the campaign solicitation will generate $471 in gross revenue. The average cost per solicitation is $66. Incorporating the above information in a decision matrix, what would be the decision threshold (probability cutoff) generated in your model?
You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

  • A. 0.86
  • B. 0.16
  • C. 0.14
  • D. 0.20
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Question #4

Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:

1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:

  • A. 14.69
  • B. 5862.76
  • C. 5.00
  • D. 67409.93
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #5

Which of the following is not a good reason to"regularize" input distributions using a simple transformation?
Response:

  • A. Regression models are sensitive to extreme or outlying values in the input space.
  • B. One benefit is improved model performance.
  • C. Another benefit is ease in model interpretation.
  • D. When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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