SASInstitute Modeling Using SAS Visual Statistics : A00-485 valid dump

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SASInstitute A00-485 Exam Syllabus Topics:

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What can be interpreted from the Summary Table for model comparison, including statistics and variable importance?

A) Model performance metrics and their relative importance
B) The distribution of predictor variables
C) The number of iterations performed by each model
D) The correlation matrix of predictor variables

2. In SAS Visual Analytics, which of the following tasks involves converting a categorical variable into a numerical one?

A) Creating a dummy variable
B) Aggregating a measure
C) Transforming a variable
D) Replacing dirty data

3. What conditions might make models less comparable in SAS Visual Statistics?

A) If they use the same dataset and response variable
B) If they have similar AUC values
C) If they have different learning rates
D) If they are both logistic regression models

4. What is the primary goal of linear models in statistical modeling?

A) To predict categorical outcomes
B) To classify data into distinct groups
C) To capture non-linear relationships in data
D) To establish a linear relationship between variables

5. In group-by modeling, when is the p-value for the group-by variable considered significant?

A) When the p-value is less than 0.05
B) When the p-value is exactly 0.05
C) When the p-value is greater than 0.05
D) When the p-value is less than 0.01

Solutions: