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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What does it mean to create dummy variables in SAS Visual Data Builder?

A) Aggregating multiple measures into one variable
B) Generating artificial data points
C) Replacing missing values with zeros
D) Converting categorical variables into binary variables

2. Which statement is true about performing regressions in SAS Visual Statistics?

A) You can specify an ordinal classifier as the response variable with linear regression.
B) You can specify a multinomial classifier as the response variable with linear regression.
C) You can build neither a linear regression nor a logistic regression with a generalized linear model.
D) You can build both a linear regression or a logistic regression with a generalized linear model.

3. What is the primary purpose of concordance statistics in model comparison?

A) To measure the balance between sensitivity and specificity
B) To calculate the p-values of predictor variables
C) To evaluate the relationship between two predictor variables
D) To assess the multicollinearity among predictors

4. Refer to the exhibit from a linear regression model in SAS Visual Statistics.

Based on the table above and assuming a significance level of 0.05, what can be concluded about the linear regression model?

A) The Intercept is an important predictor of the response.
B) For a .03696 unit decrease in RunPulse, there is an expected one-unit increase in the response.
C) For one one-unit increase in RunTime, there is an expected increase in the response of 2.6287.
D) RestPulse is a significant predictor of the response.

5. What is variable selection in SAS Visual Statistics used for in logistic regression modeling?

A) To identify and choose relevant predictor variables
B) To exclude all predictor variables
C) To assign roles to variables
D) To specify the distribution of the response variable

Solutions: