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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.

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%

  • Detect and analyze interactions between factors
  • Verify the assumptions of ANOVA
  • 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%

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

4. Prepare Inputs for Predictive Model Performance - 20%

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

5. Measure Model Performance - 25%

  • Establish effective decision cut-off values for scoring
  • 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

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.

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SASInstitute A00-240 Exam Syllabus Topics:

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

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