When performing decision tree analysis in SAS Visual Statistics, how does the property setting for
"include missing" modify the usage of missing values within categorical discrete predictors?

• A.assigns the smallest available machine value
• B.imputes the median of the predictor's known values
• C.imputes the mean of the predictor's known values
• D.assigns its own level

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What is the primary purpose of modeling effects in linear regression?

• A.To assess multicollinearity among predictors
• B.To capture the relationship between predictors and the response variable
• C.To calculate the p-values of the predictors
• D.To identify outliers in the data

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What does the Variable Importance feature help with when choosing the best fitting group-by model?

• A.Understanding the distribution of the target variable
• B.Evaluating the multicollinearity among predictors
• C.Assessing the significance of each predictor
• D.Identifying the most influential predictors

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Which statement is true for negative binomial and Poisson regression models?

• A.The canonical link function for Poisson regression is the log, while for negative binomial it is the logit.
• B.Negative binomial models accommodate negative integers while Poisson regression does not.
• C.Poisson regression is a special case of negative binomial regression.
• D.Poisson regression models are used for count data, and negative binomial models are used for binary responses.

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You would like to see the minimum and maximum values for all of your measures so that you can filter variables as needed.
Which is the most efficient way to do that?

• A.Create aggregated measures using the Min and Max aggregations.
• B.Create a calculated item subtracting the Min aggregation from the Max aggregation.
• C.Select a histogram object for each measure.
• D.Select View Measure Details within the Actions menu to the right of the dataset name.

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