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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

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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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.

What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

  • 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
  • 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)
  • Passing score: 68% (Must achieve score of 68 percent correct to pass)
  • Length of Examination: 120 minutes

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

SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Prepare Inputs for Predictive Model Performance20%- Variable Engineering and Screening
  • 1. Identify nonlinear associations using CORR procedure
  • 2. Improve predictive power of categorical variables
  • 3. Screen variables for irrelevance
  • 4. Use empirical logit plots for nonlinearity detection
- Data Preparation
  • 1. Use loops, arrays, functions and conditional statements
  • 2. Identify challenges in preparing model input data
  • 3. Manipulate data using DATA step programming
Measure Model Performance25%- Validation and Selection
  • 1. Compare and select predictive models
  • 2. Perform model validation using training and validation data
- Decision Optimization
  • 1. Evaluate scoring strategies
  • 2. Establish effective decision cutoff values
- Model Assessment
  • 1. Apply principles of honest assessment
  • 2. Assess classifier performance using confusion matrices
- Performance Visualization
  • 1. Create and interpret ROC charts
  • 2. Create and interpret lift charts
  • 3. Create and interpret gains charts
ANOVA10%- ANOVA Concepts and Assumptions
  • 1. Verify ANOVA assumptions
  • 2. Identify appropriate ANOVA methods
- ANOVA Analysis
  • 1. Analyze differences between population means using GLM and TTEST procedures
  • 2. Detect and analyze factor interactions
  • 3. Perform post hoc tests
  • 4. Evaluate treatment effects
Logistic Regression25%- Interpret and Deploy Models
  • 1. Interpret LOGISTIC procedure output
  • 2. Score new data sets using LOGISTIC and PLM procedures
- Develop Logistic Models
  • 1. Optimize model performance through input selection
  • 2. Perform logistic regression using the LOGISTIC procedure
Linear Regression20%- Build Regression Models
  • 1. Fit multiple linear regression models
  • 2. Use REG and GLM procedures
- Interpret Regression Results
  • 1. Evaluate parameter estimates
  • 2. Interpret REG, PLM and GLM output
- Model Selection and Diagnostics
  • 1. Assess model validity
  • 2. Perform model selection using REG or GLMSELECT
  • 3. Conduct residual and diagnostic analysis

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