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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
- England - 46,632 POUND
- United State - 70,247 USD
- India - 8,42,327 INR
- Europe - 45,347 EURO
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.
SASInstitute A00-240 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Linear Regression | 20% | - Perform model selection with GLMSELECT - Conduct residual and diagnostic analysis - Interpret REG, GLM, and PLM procedure output - Fit multiple linear regression models |
| 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 |
| Measure and Evaluate Model Performance | 25% | - Validate models with training/validation data - Use confusion matrices and classification metrics - Determine optimal decision cut-off values - Create and interpret ROC, lift, and gains charts - Apply honest assessment principles |
| Analysis of Variance (ANOVA) | 10% | - Assess ANOVA assumptions - Perform post-hoc tests - Analyze factor interactions - Use PROC GLM for ANOVA |
| Logistic Regression | 25% | - Interpret odds ratios and model coefficients - Score new datasets with LOGISTIC and PLM - Select and optimize input variables - Build models using PROC LOGISTIC |
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