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)
- Format: Multiple choices, multiple answers , short answers
- 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
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A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification Path
The A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification is one of the highest level of certification mainly focussing to the Advanced statistical analysis.
if you pass your exam and meet all requirements for a credential, you will receive an e-mail from SAS within 72 business hours with instructions providing access to your certificate and logo through the SAS Certification Manager. You will also receive an email from Acclaim with access to your digital badge. For questions regarding access to either of these, please visit SAS Website.
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The registration for the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam follows the steps given below.
- Step 1 : Visit to website Pearson VUE
- Step 2 : Navigate To Certifications
- Step 3 : Search for the exam name A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling
- Step 4 : Book the exam.
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SASInstitute A00-240 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Logistic Regression | - Model fit and diagnostics - Binary logistic regression |
| Topic 2: Multiple Regression | - Interaction effects - Multicollinearity diagnostics - Model building and selection |
| Topic 3: Simple Linear Regression | - Estimation and inference - Residual analysis - Model assumptions and interpretation |
| Topic 4: ANOVA and General Linear Models | - One-way and multi-way ANOVA - GLM procedures in SAS |
| Topic 5: Model Diagnostics and Validation | - Goodness-of-fit measures - Influence and leverage |

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