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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
- 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)
- 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
- Length of Examination: 120 minutes
- Passing score: 68% (Must achieve score of 68 percent correct to pass)
- Format: Multiple choices, multiple answers , short answers
How much A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam cost
A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam cost is $180.
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Who should take the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
Individuals should pursue the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam if they want to demonstrate their expertise and ability to access and manage data to perform queries and analyses from A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification
- Stastical Analyst, or
- Business Analyst
- Anyone writing & interested in Statistical Business Analysis
SASInstitute A00-240 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare Inputs for Predictive Modeling | 20% | - Screen variables with CORR procedure and empirical logit plots - Transform categorical variables - Identify data preparation challenges - Manipulate data using DATA step |
| Topic 2: Measure and Evaluate Model Performance | 25% | - Validate models with training/validation data - Apply honest assessment principles - Create and interpret ROC, lift, and gains charts - Use confusion matrices and classification metrics - Determine optimal decision cut-off values |
| Topic 3: Linear Regression | 20% | - Interpret REG, GLM, and PLM procedure output - Perform model selection with GLMSELECT - Conduct residual and diagnostic analysis - Fit multiple linear regression models |
| Topic 4: Logistic Regression | 25% | - Select and optimize input variables - Build models using PROC LOGISTIC - Interpret odds ratios and model coefficients - Score new datasets with LOGISTIC and PLM |
| Topic 5: Analysis of Variance (ANOVA) | 10% | - Perform post-hoc tests - Assess ANOVA assumptions - Use PROC GLM for ANOVA - Analyze factor interactions |
