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How to book A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exams

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.

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

How to study the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

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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

  • Anyone writing & interested in Statistical Business Analysis
  • Stastical Analyst, or
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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

  • Length of Examination: 120 minutes
  • 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)
  • Format: Multiple choices, multiple answers , short answers
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SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Prepare Inputs for Predictive Modeling20%- Manipulate data using DATA step
- Screen variables with CORR procedure and empirical logit plots
- Transform categorical variables
- Identify data preparation challenges
Analysis of Variance (ANOVA)10%- Use PROC GLM for ANOVA
- Perform post-hoc tests
- Analyze factor interactions
- Assess ANOVA assumptions
Linear Regression20%- Fit multiple linear regression models
- Conduct residual and diagnostic analysis
- Interpret REG, GLM, and PLM procedure output
- Perform model selection with GLMSELECT
Logistic Regression25%- Select and optimize input variables
- Build models using PROC LOGISTIC
- Interpret odds ratios and model coefficients
- Score new datasets with LOGISTIC and PLM
Measure and Evaluate Model Performance25%- Determine optimal decision cut-off values
- Use confusion matrices and classification metrics
- Create and interpret ROC, lift, and gains charts
- Apply honest assessment principles
- Validate models with training/validation data

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