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What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam
- 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
- 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)
- Length of Examination: 120 minutes
- Passing score: 68% (Must achieve score of 68 percent correct to pass)
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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%
- Perform ANOVA post hoc test to evaluate treatment effect
- Analyze differences between population means using the GLM and TTEST procedures
- Verify the assumptions of ANOVA
- Detect and analyze interactions between factors
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
- Assess the validity of a given regression model through the use of diagnostic and residual analysis
- Fit a multiple linear regression model using the REG and GLM procedures
3. Logistic Regression - 25%
- Score new data sets using the LOGISTIC and PLM procedures
- Interpret the output of the LOGISTIC procedure
- Optimize model performance through input selection
- Perform logistic regression with the LOGISTIC procedure
4. Prepare Inputs for Predictive Model Performance - 20%
- Identify the potential challenges when preparing input data for a model
- Screen variables for non-linearity using empirical logit plots
- Use the DATA step to manipulate data with loops, arrays, conditional statements and functions
- Improve the predictive power of categorical inputs
- Screen variables for irrelevance and non-linear association using the CORR procedure
5. Measure Model Performance - 25%
- Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
- Model selection and validation using training and validation data
- Apply the principles of honest assessment to model performance measurement
- Establish effective decision cut-off values for scoring
- Assess classifier performance using the confusion matrix
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.
SASInstitute A00-240 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Measure and Evaluate Model Performance | 25% | - Create and interpret ROC, lift, and gains charts - Use confusion matrices and classification metrics - Apply honest assessment principles - Validate models with training/validation data - Determine optimal decision cut-off values |
| Topic 2: Prepare Inputs for Predictive Modeling | 20% | - Screen variables with CORR procedure and empirical logit plots - Identify data preparation challenges - Transform categorical variables - Manipulate data using DATA step |
| Topic 3: Analysis of Variance (ANOVA) | 10% | - Analyze factor interactions - Perform post-hoc tests - Assess ANOVA assumptions - Use PROC GLM for ANOVA |
| Topic 4: Logistic Regression | 25% | - Select and optimize input variables - Interpret odds ratios and model coefficients - Score new datasets with LOGISTIC and PLM - Build models using PROC LOGISTIC |
| Topic 5: Linear Regression | 20% | - Conduct residual and diagnostic analysis - Interpret REG, GLM, and PLM procedure output - Fit multiple linear regression models - Perform model selection with GLMSELECT |
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