SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential: A00-240 Exam


"SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential", also known as A00-240 exam, is a SASInstitute Certification. With the complete collection of questions and answers, PrepAwayPDF has assembled to take you through 100 Q&As to your A00-240 Exam preparation. In the A00-240 exam resources, you will cover every field and category in SAS Institute Systems Certification Certification helping to ready you for your successful SASInstitute Certification.

  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Total Questions: 100

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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

  • Anyone writing & interested in Statistical Business Analysis
  • Business Analyst
  • Stastical Analyst, or

Topics of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Dumps will include the following topics:

1. ANOVA - 10%

  • Verify the assumptions of ANOVA
  • Detect and analyze interactions between factors
  • Perform ANOVA post hoc test to evaluate treatment effect
  • Analyze differences between population means using the GLM and TTEST procedures

2. Linear Regression - 20%

  • Use the REG or GLMSELECT procedure to perform model selection
  • Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models
  • Fit a multiple linear regression model using the REG and GLM procedures
  • Assess the validity of a given regression model through the use of diagnostic and residual analysis

3. Logistic Regression - 25%

  • Score new data sets using the LOGISTIC and PLM procedures
  • Perform logistic regression with the LOGISTIC procedure
  • Optimize model performance through input selection
  • Interpret the output of the LOGISTIC procedure

4. Prepare Inputs for Predictive Model Performance - 20%

  • Improve the predictive power of categorical inputs
  • Use the DATA step to manipulate data with loops, arrays, conditional statements and functions
  • Screen variables for non-linearity using empirical logit plots
  • Screen variables for irrelevance and non-linear association using the CORR procedure
  • Identify the potential challenges when preparing input data for a model

5. Measure Model Performance - 25%

  • Model selection and validation using training and validation data
  • Assess classifier performance using the confusion matrix
  • Apply the principles of honest assessment to model performance measurement
  • Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
  • Establish effective decision cut-off values for scoring

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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.

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

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

Preparation Guide for A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Introduction

SAS (previously “Statistical Analysis System”) may be a package suite designed by SAS Institute for advanced analytics, variable analyses, business intelligence, knowledge management, and prognosticative analytics.

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling exam is administered by SAS and Pearson VUE. has created a track for IT professionals to certify as business analyst on SAS. This certification program provides SAS professionals a way to demonstrate their skills. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets SAS's proficiency standards.

SAS® Certified Statistical Business Analyst for SAS®9 this credential is for professionals who use SAS/STAT® software to conduct and interpret complex statistical data analysis.

In this guide, we will cover the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam, A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certified professional's salary and all aspects of the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification.

The SAS international Certification Program currently issues versioned accreditation that don't lapse.The version is indicated in the credential name.

SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare Inputs for Predictive Model Performance20%- Variable Engineering and Screening
  • 1. Screen variables for irrelevance
  • 2. Use empirical logit plots for nonlinearity detection
  • 3. Identify nonlinear associations using CORR procedure
  • 4. Improve predictive power of categorical variables
- Data Preparation
  • 1. Identify challenges in preparing model input data
  • 2. Use loops, arrays, functions and conditional statements
  • 3. Manipulate data using DATA step programming
Topic 2: Logistic Regression25%- Interpret and Deploy Models
  • 1. Score new data sets using LOGISTIC and PLM procedures
  • 2. Interpret LOGISTIC procedure output
- Develop Logistic Models
  • 1. Optimize model performance through input selection
  • 2. Perform logistic regression using the LOGISTIC procedure
Topic 3: Measure Model Performance25%- Decision Optimization
  • 1. Establish effective decision cutoff values
  • 2. Evaluate scoring strategies
- Validation and Selection
  • 1. Compare and select predictive models
  • 2. Perform model validation using training and validation data
- Performance Visualization
  • 1. Create and interpret lift charts
  • 2. Create and interpret gains charts
  • 3. Create and interpret ROC charts
- Model Assessment
  • 1. Assess classifier performance using confusion matrices
  • 2. Apply principles of honest assessment
Topic 4: Linear Regression20%- Interpret Regression Results
  • 1. Interpret REG, PLM and GLM output
  • 2. Evaluate parameter estimates
- Model Selection and Diagnostics
  • 1. Perform model selection using REG or GLMSELECT
  • 2. Conduct residual and diagnostic analysis
  • 3. Assess model validity
- Build Regression Models
  • 1. Fit multiple linear regression models
  • 2. Use REG and GLM procedures
Topic 5: ANOVA10%- ANOVA Analysis
  • 1. Evaluate treatment effects
  • 2. Perform post hoc tests
  • 3. Detect and analyze factor interactions
  • 4. Analyze differences between population means using GLM and TTEST procedures
- ANOVA Concepts and Assumptions
  • 1. Verify ANOVA assumptions
  • 2. Identify appropriate ANOVA methods

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