A00-240 100% Exam Coverage - Top A00-240 Questions

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SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Logistic Regression25%- Select and optimize input variables
- Score new datasets with LOGISTIC and PLM
- Interpret odds ratios and model coefficients
- Build models using PROC LOGISTIC
Analysis of Variance (ANOVA)10%- Use PROC GLM for ANOVA
- Perform post-hoc tests
- Assess ANOVA assumptions
- Analyze factor interactions
Measure and Evaluate Model Performance25%- Apply honest assessment principles
- Determine optimal decision cut-off values
- Create and interpret ROC, lift, and gains charts
- Validate models with training/validation data
- Use confusion matrices and classification metrics
Linear Regression20%- Fit multiple linear regression models
- Conduct residual and diagnostic analysis
- Interpret REG, GLM, and PLM procedure output
- Perform model selection with GLMSELECT
Prepare Inputs for Predictive Modeling20%- Screen variables with CORR procedure and empirical logit plots
- Manipulate data using DATA step
- Identify data preparation challenges
- Transform categorical variables

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Top A00-240 Questions, A00-240 Actualtest

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q25-Q30):

NEW QUESTION # 25
One common approach for predicting rare events in the LOGISTIC procedure is to build a model that disproportionately over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event split).
What problem does this present?

Answer: A


NEW QUESTION # 26
The total modeling data has been split into training, validation, and test data.
What is the best data to use for model assessment?

Answer: A


NEW QUESTION # 27
An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation,
and test sets to perform honest assessment during the model building process.
What is the purpose of the test data set?

Answer: C


NEW QUESTION # 28
What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?

Answer: B


NEW QUESTION # 29
Refer to the exhibit: The box plot was used to analyze daily sales data following three different ad campaigns.

The business analyst concludes that one of the assumptions of ANOVA was violated.
Which assumption has been violated and why?

Answer: D


NEW QUESTION # 30
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