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| Certification Vendor: | SAS Institute |
|---|---|
| Exam Name: | SAS Statistical Business Analysis Using SAS 9: Regression and Modeling |
| Exam Number: | A00-240 |
| Exam Price: | $180 USD |
| Exam Format: | Multiple Choice, Short Answer |
| Passing Score: | 68% |
| Exam Duration: | 110 minutes |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 60-65 |
| Available Languages: | Chinese (Simplified), Japanese, English |
| Related Certifications: | SAS Certified Advanced Analytics Professional Using SAS 9 |
| Recommended Training: | SAS Statistical Business Analysis Using SAS 9: Regression and Modeling SAS Exam Content Guide A00-240 |
| Exam Registration: | SAS Certification Portal Pearson VUE Registration |
| Sample Questions: | ![]() |
| Exam Way: | Computer-based testing at Pearson VUE centers or online proctored |
| Pre Condition: | No formal prerequisites; recommended knowledge of SAS programming and basic statistics |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/statistical-business-analyst.html |
| Section | Weight | Objectives |
|---|---|---|
| Linear Regression | 20% | - Fit multiple linear regression models - Interpret REG, GLM, and PLM procedure output - Perform model selection with GLMSELECT - Conduct residual and diagnostic analysis |
| Analysis of Variance (ANOVA) | 10% | - Perform post-hoc tests - Analyze factor interactions - Use PROC GLM for ANOVA - Assess ANOVA assumptions |
| Measure and Evaluate Model Performance | 25% | - Use confusion matrices and classification metrics - Validate models with training/validation data - Apply honest assessment principles - Create and interpret ROC, lift, and gains charts - Determine optimal decision cut-off values |
| Logistic Regression | 25% | - Interpret odds ratios and model coefficients - Build models using PROC LOGISTIC - Select and optimize input variables - Score new datasets with LOGISTIC and PLM |
| Prepare Inputs for Predictive Modeling | 20% | - Manipulate data using DATA step - Transform categorical variables - Screen variables with CORR procedure and empirical logit plots - Identify data preparation challenges |
SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential is an official SAS Institute exam, catalogued under the code A00-240. A pass awards you the SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification at the Specialist level. It also supports progress toward SAS Certified Advanced Analytics Professional Using SAS 9. Demand for this credential has stayed strong because it validates skills employers can use from day one.
The SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam packs 60-65 questions into 110 minutes. Candidates rarely fail because of one impossible topic; they fail because ten minutes vanished on three stubborn questions. Build a triage habit now: answer, flag, move on, return later. Timed full-length sessions in the ValidDumps test engine are the most honest way to practice that discipline before it counts.
You pass SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential at 68%, and the official registration fee stands at $180 USD. One detail worth internalizing: there is no retake discount, so a second sitting costs another full $180 USD. Use the ValidDumps practice tests as your gauge and book only when your results clear the requirement with a repeatable margin, not a one-off peak.
No formal prerequisites; recommended knowledge of SAS programming and basic statistics
Vendor policies shift over time, so confirm the current entry conditions before paying any registration fee; the official exam page is the authoritative source.
You can sign up for SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential through the official registration points listed here.
Regarding format, the exam is delivered Computer-based testing at Pearson VUE centers or online proctored.
SAS Institute recommends the following training for SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential candidates.
Course content builds understanding, but the exam grades answers. Bridge the two with the 100 practice questions in the ValidDumps A00-240 package, and the theory starts converting into points.
Yes. A free demo of the SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential material is available on this page, so you can verify the quality of the questions and the expert-edited answers yourself. Once you purchase, updates are free for 365 days and the newest version is emailed to you automatically as it releases; after expiry, extending the update service costs 50% of the regular price.
A 100% money-back guarantee covers your purchase under defined conditions. If you take the SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential exam within 60 days of buying and fail, you can claim a full refund, provided the exam matches your product. Attempts within 3 days of purchase are ineligible, as are downloaded-but-unused products, free materials, and expired orders, and the candidate name must match the payer name. Submit a scanned enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, you may exchange rather than refund: two other exam products of equal value, free, with the update service on your original purchase kept intact.
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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential spans 5 official domains. The most heavily weighted include Prepare Inputs for Predictive Modeling (20%), Analysis of Variance (ANOVA) (10%), and Logistic Regression (25%). The full topic list is published above on this page; let the weightings decide where your next study hour goes.
Question 1
The selection criterion used in the forward selection method in the GLMSELECT procedure is:
A. MSE
B. R-squared
C. RSQ
D. AIC
Question 2
What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?
A. It violates assumptions of the model.
B. There is no ability to compare the effectiveness of different cleansing methods.
C. It requires extra computational effort and time.
D. It omits the training (and test) data sets from the benefits of the cleansing methods.
Question 3
Refer to the exhibit:
An analyst examined logistic regression models for predicting whether a customer would make a purchase.
The ROC curve displayed summarizes the models. Using the selected model and the analyst's decision rule,
25% of the customers who did not make a purchase are incorrectly classified as purchasers.
What can be concluded from the graph?
A. About 25% of the customers who did make a purchase are correctly classified as making a purchase.
B. About 85% of the customers who did make a purchase are correctly classified as making a purchase.
C. About 95% of the customers who did make a purchase are correctly classified as making a purchase.
D. About 50% of the customers who did make a purchase are correctly classified as making a purchase.
Question 4
What is the default method in the LOGISTIC procedure to handle observations with missing data?
A. Only cases with variables that are fully populated are used.
B. Parameter estimates are made on all available data.
C. Parameters are estimated accounting for the missing values.
D. Missing values are imputed.
Question 5
The Model SS in a multiple linear regression model is equal to:
A. the sum of Type II SS of all model terms
B. the sum of Type I SS of all model terms
C. the total SS- MSE
D. the sum of SSE and MSE
Solutions:
| Question 1 Answer: D | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: A | Question 5 Answer: B |
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