Free SAS Statistical Business Analysis SAS9: Regression and Model Exam A00-240 Exam Practice Test

In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

• Training: 50% Validation: 0% Testing: 50%
• Training: 100% Validation: 0% Testing: 0%
• Training: 0% Validation: 100% Testing: 0%
• Training: 50% Validation: 50% Testing: 0%

The SAS data set RESULT contains the following variables:Region (GrpA or GrpB) Sales (dollars per year)Which SAS programs can be used to find the p-value for comparing GrpA sales with GrpB sales? (Choose two.)

• Option A
• Option B
• Option C
• Option D

What is a benefit to performing data cleansing (imputation, transformations, etc.) on data after partitioning the data for honest assessment as opposed to performing the data cleansing prior to partitioning the data?

• It makes inference on the model possible.
• It is computationally easier and requires less time.
• It omits the training (and test) data sets from the benefits of the cleansing methods.
• It allows for the determination of the effectiveness of the cleansing method.

The Model SS in a multiple linear regression model is equal to:

• the total SS- MSE
• the sum of Type I SS of all model terms
• the sum of Type II SS of all model terms
• the sum of SSE and MSE

While building a predictive model, median imputations are performed while preparing the training data.How should the imputations be addressed in the validation data?

• The imputed values are irrelevant to the validation data, and are not used.
• The imputed values must be applied directly to the validation data without recalculation.
• The imputed values must be recalculated using the validation data.
• The imputed values must be recalculated using both the training and the validation data.

This question will ask you to provide a missing option.Complete the following syntax to test the homogeneity of variance assumption in the GLM procedure:means Region / <insert option here> =levene ;

• test
• adjust
• var
• hovtest

Refer to the lift chart:What does the reference line at lift = 1 corresponds to?

• The predicted lift for the best 50% of validation data cases
• The predicted lift if the entire population is scored as event cases
• The predicted lift if none of the population are scored as event cases
• The predicted lift if 50% of the population are randomly scored as event cases

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

• Training data
• Total data
• Test data
• Validation data

Screening for non-linearity in binary logistic regression can be achieved by visualizing:

• A scatter plot of binary response versus a predictor variable.
• A trend plot of empirical logit versus a predictor variable.
• A logistic regression plot of predicted probability values versus a predictor variable.
• A box plot of the odds ratio values versus a predictor variable.

A researcher has several variables that could be possible predictors for the final model. There is interest in checking all 2-way interactions for possible entry to the model. The researcher has decided to use forward selection within PROC LOGISTIC. Fill in the missing code option that will ensure that all 2-way interactions will be considered for entry.

• start = 5
• include = 4
• include = 5
• start = 4