SASInstitute A00-240 Accurate Test - Exam A00-240 Simulator Online

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SASInstitute A00-240 Exam Overview:
| Certification Vendor: | SAS Institute |
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| Exam Name: | SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Exam |
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| Exam Number: | A00-240 |
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| Passing Score: | Approximately 70% |
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| Exam Price: | $180 USD (varies by region) |
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| Exam Duration: | 120-135 |
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| Related Certifications: | SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling SAS Certified Base Programmer for SAS 9 SAS Certified Advanced Programmer for SAS 9 |
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| Exam Format: | Multiple Choice, Multiple Response, Computer-Based Exam (Proctored) |
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| Certificate Validity Period: | 3 years |
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| Real Exam Qty: | 50-60 |
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| Available Languages: | English |
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| Recommended Training: | SAS Regression and Modeling Training |
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| Exam Registration: | SAS Certification Registration |
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| Sample Questions: | SASInstitute A00-240 Sample Questions |
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| Exam Way: | Computer-based proctored exam (online or test center) |
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| Pre Condition: | Recommended: SAS Certified Base Programmer for SAS 9 or equivalent experience with SAS programming and statistical methods. |
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| Official Syllabus URL: | https://www.sas.com/en_us/certification.html |
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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SASยฎ9:Regression and Modeling Exam
- Passing score: 68% (Must achieve score of 68 percent correct to pass)
- Language: Czech, simplified Chinese, traditional Chinese, Dutch, English (UK), English (US), French, German, Indonesian, Italian, Japanese, Korean, Polish, Portuguese, Portuguese (Brazil), Russian, Slovak, Spanish, Spanish (Latin America), Thai, Turkish, and Vietnamese
- Number of Questions: 60 multiple-choice and short-answer questions(In addition to the 60 scored items, there may be up to five unscored items)
- Length of Examination: 120 minutes
- Format: Multiple choices, multiple answers , short answers
SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q53-Q58):
NEW QUESTION # 53
Refer to the exhibit.

These graphs were created using the GLM procedure with the plots(only)=diagnosticsoption.
Which plot do you use to identify influential observations?
- A. Residual by Quantile
- B. Fit - Mean and Residual Plot
- C. Residual by Predicted
- D. Cook's D by Observation
Answer: D
Explanation:
Explanation/Reference: https://books.google.com.pk/books?id=fx77Pzerty8C&pg=PA279&lpg=PA279&dq=sas+statistical
+analysis+plot+do+you+use+to+identify+influential
+observations&source=bl&ots=AJavSAql_g&sig=ACfU3U0jbAa6lTWvSeSJ6y5bwp4osAyigA&hl=en&sa=X&ve d=2ahUKEwje34nyqajnAhXDThUIHUfUCj0Q6AEwEXoECAoQAQ#v=onepage&q=sas%20statistical%
20analysis%20plot%20do%20you%20use%20to%20identify%20influential%20observations&f=false
NEW QUESTION # 54
The total modeling data has been split into training, validation, and test data. What is the best data to use for model assessment?
- A. Validation data
- B. Test data
- C. Total data
- D. Training data
Answer: A
NEW QUESTION # 55
What is the default method in the LOGISTIC procedure to handle observations with missing data?
- A. Missing values are imputed.
- B. Parameter estimates are made on all available data.
- C. Only cases with variables that are fully populated are used.
- D. Parameters are estimated accounting for the missing values.
Answer: C
NEW QUESTION # 56
Given the following LOGISTIC procedure:

What is the difference between the datasets OUTFILEJ and OUTFILE_2?
- A. OUTFILEJ contains the final parameter estimates and Wald Chi-Square values while OUTFILE_2 contains the newly scored probabilities.
- B. OUTFILE_1 contains the final parameter estimates while OUTFILE_2 contains the newly scored probabilities.
- C. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored probabilities
- D. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored logits.
Answer: B
NEW QUESTION # 57
This question will ask you to provide missing code segments.
A logistic regression model was fit on a data set where 40% of the outcomes were events (TARGET=1) and 60% were non-events (TARGET=0). The analyst knows that the population where the model will be deployed has 5% events and 95% non-events. The analyst also knows that the company's profit margin for correctly targeted events is nine times higher than the company's loss for incorrectly targeted non-event.
Given the following SAS program:

What X and Y values should be added to the program to correctly score the data?
- A. X=.05, Y=.40
- B. X=.05, Y=10
- C. X=.10.Y=05
- D. X=40, Y=10
Answer: B
NEW QUESTION # 58
......
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