SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential: A00-240 Exam


"SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential", also known as A00-240 exam, is a SASInstitute Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 100 Q&As to your A00-240 Exam preparation. In the A00-240 exam resources, you will cover every field and category in SAS Institute Systems Certification Certification helping to ready you for your successful SASInstitute Certification.

  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Total Questions: 100

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A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certified Professional salary

The average salary of a A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certified Expert in

  • India - 8,42,327 INR
  • United State - 70,247 USD
  • England - 46,632 POUND
  • Europe - 45,347 EURO

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
  • 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
  • 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

Reference: https://www.sas.com/en_us/certification/credentials/advanced-analytics/statistical-business-analyst.html

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SASInstitute A00-240 Exam Syllabus Topics:

SectionObjectives
ANOVA and General Linear Models- One-way and multi-way ANOVA
- GLM procedures in SAS
Simple Linear Regression- Model assumptions and interpretation
- Residual analysis
- Estimation and inference
Logistic Regression- Model fit and diagnostics
- Binary logistic regression
Multiple Regression- Model building and selection
- Interaction effects
- Multicollinearity diagnostics
Model Diagnostics and Validation- Influence and leverage
- Goodness-of-fit measures

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