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SASInstitute A00-240

A00-240

Exam Code: A00-240

Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential

Updated: Aug 21, 2026

Q & A: 100 Questions and Answers

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About SASInstitute A00-240 Exam

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
  • Anyone writing & interested in Statistical Business Analysis
  • Business Analyst

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)
  • Passing score: 68% (Must achieve score of 68 percent correct to pass)
  • Length of Examination: 120 minutes
  • Format: Multiple choices, multiple answers , short answers
  • 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

In recent years, many people choose to take SASInstitute A00-240 certification exam which can make you get the SASInstitute certificate that is the passport to get a better job and get promotions.

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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

  • Europe - 45,347 EURO
  • United State - 70,247 USD
  • England - 46,632 POUND
  • India - 8,42,327 INR

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

Preparation of certification exams could be covered with two resource types . The first one are the study guides, reference books and study forums that are elaborated and appropriate for building information from ground up. Apart from them video tutorials and lectures are a good option to ease the pain of through study and are relatively make the study process more interesting nonetheless these demand time and concentration from the learner. Smart candidates who wish to create a solid foundation altogether examination topics and connected technologies typically mix video lectures with study guides to reap the advantages of each but practice exams or practice exam engines is one important study tool which goes typically unnoted by most candidates. Practice exams are designed with our experts to make exam prospects test their knowledge on skills attained in course, as well as prospects become comfortable and familiar with the real exam environment. Statistics have indicated exam anxiety plays much bigger role of students failure in exam than the fear of the unknown. Itcerttest expert team recommends preparing some notes on these topics along with it don't forget to practice A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam exam dumps which had been written by our expert team, each of these can assist you loads to clear this exam with excellent marks.

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

SASInstitute A00-240 Exam Syllabus Topics:

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

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