Understanding Residuals in Regression Analysis

What does a residual represent in regression analysis?

• The total number of data points

• The sum of all errors

• The difference between actual and predicted values

• The average of predicted values

How is a residual calculated?

• By multiplying the actual value by the predicted value

• By subtracting the predicted value from the actual value

• By dividing the actual value by the predicted value

• By adding the actual and predicted values

In the example with study time and GPA, what was the residual when the actual GPA was 3.5 and the predicted GPA was 3?

• 0.5

• 1.5

• 3.5

• 2.5

What does a positive residual indicate about the actual value's position relative to the regression line?

• It is below the regression line

• It is above the regression line

• It is on the regression line

• It is unrelated to the regression line

What does a negative residual tell us about the actual value?

• It is below the regression line

• It is unrelated to the regression line

• It is above the regression line

• It is equal to the predicted value