(2pts) An individual is using linear regression to predict the total points scored in a basketball game from the home team's offensive efficiency (HOffEff), the home team's defensive efficiency (HDefEff), the away team's offensive efficiency (AOffEff), and the away team's defensive efficiency (ADefEff). He assumes the model



Pointsi = α + β1HOffEffi + β2HDefEffi + β3AOffEffi + β4ADefEffi + εi



Which of the following is necessary for the regression model to minimize the sums of squares of the residuals?



multiple choice
The ε terms are all independent of each other
The ε terms all have mean 0
The ε terms all have the same standard deviation
The ε terms are all normally distributed
All of the first four conditions must hold
All of the first four conditions must hold, plus the model must be correctly specified
Regression will always minimize the sum of squares of residuals
Regression will never minimize the sum of squares of residuals
Regression may or may not minimize the sum of squares of the residuals depending on the structure of the data Incorrect