0.065 L =65 cL.

Jeff then ran the following regression of ratings on the indicator of generalmills and the nutritional variables of calories, fiber, and sugars:

Calculate a 95% prediction interval for the wine quality in a new batch of Camille’s red wine with a fixed acidity of 10, a residual sugar of 2.5, a density of .995, and an alcohol content of 11.

8 kL = 8000 L  

Which of the following most likely explains why the intercept coefficient is a negative number?

7.5 L = 75000 mL  

Which of the following is a correct interpretation of the coefficient on generalmills in the multivariate regression context?

Based on the correlation matrix, is multicollinearity likely an issue?

Based on the regression output, which of the following is a valid justification for why the coefficients on max and min resolution are negative?

Which of the following are possible consequences of tests of the residuals failing?