Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
Certification Provider: SASInstitute
Corresponding Certification: SAS Institute Systems Certification
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SASInstitute A00-240 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analysis of Variance (ANOVA) | 10% | - Assess ANOVA assumptions - Perform post-hoc tests - Analyze factor interactions - Use PROC GLM for ANOVA |
| Topic 2: Linear Regression | 20% | - Interpret REG, GLM, and PLM procedure output - Perform model selection with GLMSELECT - Fit multiple linear regression models - Conduct residual and diagnostic analysis |
| Topic 3: Logistic Regression | 25% | - Interpret odds ratios and model coefficients - Select and optimize input variables - Score new datasets with LOGISTIC and PLM - Build models using PROC LOGISTIC |
| Topic 4: Prepare Inputs for Predictive Modeling | 20% | - Manipulate data using DATA step - Transform categorical variables - Identify data preparation challenges - Screen variables with CORR procedure and empirical logit plots |
| Topic 5: Measure and Evaluate Model Performance | 25% | - Create and interpret ROC, lift, and gains charts - Determine optimal decision cut-off values - Apply honest assessment principles - Use confusion matrices and classification metrics - Validate models with training/validation data |
A00-240 Exam Questions Answered
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The SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential is delivered Computer-based testing at Pearson VUE centers or online proctored — select whichever arrangement suits you when booking.
The SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential blueprint spans 5 domains — including Prepare Inputs for Predictive Modeling (20%), Measure and Evaluate Model Performance (25%), Linear Regression (20%). Let the weightings direct your spare-time review; the full outline above lists every subtopic.
Yes — download the free SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential demo and evaluate the material before paying. Purchases include 365 days of free updates, each new version emailed immediately upon release; renew afterward at 50% off.
No formal prerequisites; recommended knowledge of SAS programming and basic statistics Eligibility rules change periodically, so confirm the current requirements on the official page (official A00-240 exam page) before registering.
Yes:
- SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
- SAS Exam Content Guide A00-240
Courses give you the theory; the 100 practice questions for the SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential give you the rehearsal — every answer expert-verified.
The SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential is SASInstitute's certification exam for SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential, at the Specialist level. It validates job-ready skills, and passing it marks you as a verified professional. Related credentials include SAS Certified Advanced Analytics Professional Using SAS 9.
$180 USD per attempt, 68% to pass. A retake costs the full fee again — effective preparation with the 100 practice questions for the A00-240 exam is the economical path.
SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions:
Refer to the exhibit.
Output from a multiple linear regression analysis is shown.
What is the most appropriate statement concerning collinearity between the input variables?
- A. Collinearity is not a problem since all Pr>|t| values are less than 0.05.
- B. Collinearity is not a problem since all variance inflation values are less than 10.
- C. Collinearity is a problem since all variance inflation values are less than 10.
- D. Collinearity is a problem since all Pr>|t| values are less than 0.05.
Correct Answer: A 🗳️
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. Missing values are imputed.
- C. Parameter estimates are made on all available data.
- D. Parameters are estimated accounting for the missing values.
Correct Answer: A 🗳️
Refer to the exhibit:
SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each subset are given.
Based on the exhibit, which statement is true?
- A. Adjusted R-Square and R-Square agree on the champion model.
- B. The AIC champion model is more parsimonious than the SBC champion.
- C. The SBC champion model is more parsimonious than the AIC champion.
- D. The R-Square champion model is the most parsimonious.
Correct Answer: C 🗳️
A marketing manager attempts to determine those customers most likely to purchase additional products as the result of a nation-wide marketing campaign.
The manager possesses a historical dataset (CAMPAIGN) of a similar campaign from last year.
It has the following characteristics:
* Target variable Respond (0, 1)
* Continuous predictor Income
* Categorical predictor Homeowner(Y, N)
Which SAS program performs this analysis?
- A. Option A
- B. Option D
- C. Option C
- D. Option B
Correct Answer: A 🗳️
Screening for non-linearity in binary logistic regression can be achieved by visualizing:
- A. A logistic regression plot of predicted probability values versus a predictor variable.
- B. A trend plot of empirical logit versus a predictor variable.
- C. A box plot of the odds ratio values versus a predictor variable.
- D. A scatter plot of binary response versus a predictor variable.
Correct Answer: B 🗳️
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