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• United State - 70,247 USD
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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
• Passing score: 68% (Must achieve score of 68 percent correct to pass)
• 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
• 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

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
• Analyze differences between population means using the GLM and TTEST procedures
• Perform ANOVA post hoc test to evaluate treatment effect

2. Linear Regression - 20%

• 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
• Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models
• Use the REG or GLMSELECT procedure to perform model selection

3. Logistic Regression - 25%

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

4. Prepare Inputs for Predictive Model Performance - 20%

• Screen variables for non-linearity using empirical logit plots
• 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
• 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
• Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
• Apply the principles of honest assessment to model performance measurement
• Assess classifier performance using the confusion matrix

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

SASInstitute A00-240 Exam Syllabus Topics: