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Introduction to A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
According to SAS, SAS® Certified Statistical Business Analyst for SAS®9 this credentials signifies the upper echelon of SAS programmers who demonstrate a high level of proficiency in SAS® programming expertise.
A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Statistical Business Analyst in the Company.
A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling exam covers the basic and advanced concepts of variance analysis, linear and logistic regression, preparing inputs for predictive models and measuring model performance.
After passing this exam, candidates get a certificate from SAS that helps them to demonstrate their proficiency in A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling to their clients and employers.
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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
- Passing score: 68% (Must achieve score of 68 percent correct to pass)
- Length of Examination: 120 minutes
- 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)
- Format: Multiple choices, multiple answers , short answers
SASInstitute A00-240 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Logistic Regression | - Model fit and diagnostics - Binary logistic regression |
| Topic 2: Simple Linear Regression | - Estimation and inference - Residual analysis - Model assumptions and interpretation |
| Topic 3: Model Diagnostics and Validation | - Goodness-of-fit measures - Influence and leverage |
| Topic 4: Multiple Regression | - Interaction effects - Model building and selection - Multicollinearity diagnostics |
| Topic 5: ANOVA and General Linear Models | - GLM procedures in SAS - One-way and multi-way ANOVA |






