1. In addition to calculating regression coefficients in a linear regression, you should also create a scatterplot to....

Check that the relationship is actually linear

None of these

Both of these

Check for outliers

2. R-squared in a multiple regression is:

the proportion of the variability in the outcome variable that can be predicted by the combination of predictors

a measurement of the strength of the model

never a negative number

all of the other options are true

3. The correlation between a particular predictor and the dependent variable, controlling for the overlap between the predictor and any other predictor(s), is called the

multiple correlation

part correlation standard error

spurious correlation