SASInstitute A00-240 dumps - in .pdf

A00-240 pdf
  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Updated: Jun 02, 2026
  • Q & A: 100 Questions and Answers
  • PDF Price: $49.99
  • Free Demo

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  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Updated: Jun 02, 2026
  • Q & A: 100 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $99.98  $69.99
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SASInstitute A00-240 dumps - Testing Engine

A00-240 Testing Engine
  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Updated: Jun 02, 2026
  • Q & A: 100 Questions and Answers
  • Software Price: $49.99
  • Testing Engine

About SASInstitute A00-240 VCE materials

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.

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SASInstitute A00-240 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Establish effective decision cut-off values for scoring
  • Fit a multiple linear regression model using the REG and GLM procedures
Topic 2
  • Identify the potential challenges when preparing input data for a model
  • Detect and analyze interactions between factors
Topic 3
  • Model selection and validation using training and validation data
  • Perform ANOVA post hoc test to evaluate treatment effect
Topic 4
  • Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
  • Use the REG or GLMSELECT procedure to perform model selection
Topic 5
  • Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models
  • Improve the predictive power of categorical inputs
Topic 6
  • Apply the principles of honest assessment to model performance measurement
  • Optimize model performance through input selection
Topic 7
  • Screen variables for non-linearity using empirical logit plots
  • Score new data sets using the LOGISTIC and PLM procedures

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

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