Say that we ran the following regression from the Used Car data set. Note that price_in_thousands is the price of a used car in thousands of dollars, horsepower is the horsepower of the used car, and fuel_efficency is the miles per gallon of the used car.

. reg price_in_thousands horsepower fuel_efficiency Source SS df MS Number of obs = 153 F (2, 150) 184.55 Model 22529.0325 2 11264.5163 Prob > F 0.0000 Residual 9155. 53441 150 61.0368961 R- squared 0. 7110 Adj R-squared 0. 7072 Total 31684.5669 152 208.451098 Root MSE = 7.8126 price_in_thou~s Coef. Std. Err. t P> | t [95% Conf. Interval] horsepower . 2195677 . 0140746 15.60 0.000 . 1917576 . 2473778 fuel efficiency . 1412474 . 1872054 0.75 0. 452 - . 2286527 . 5111476 cons -16. 62964 6. 436618 -2.58 0. 011 -29. 34778 -3.91149