Choose the dependent variable ( the response variable to be "explained") and the independent variable (the predictor or explanatory variable)

Obtain the regression equation

Y=______________X+______________

Calculate R2

R2______________

SUMMARY OUTPUT Weight City MPG Regression Statistics 3968 20 Multiple R 0.894329 3583 22 R Square 0.799824 3470 22 Adjusted R Square 0.797005 3527 23 Standard Error 2.238113 3990 18 Observations 73 4724 17 3692 21 ANOVA 3315 22 df SS MS F Significance F 3616 20 Regression 1 1421.035 1421.035 283.688 1.67E-26 5527 14 Residual 71 355.6495 5.009148 3719 16 Total 72 1776.685 3097 26 3800 19 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 3532 25 Intercept 40.08315 1.152588 34.77665 2.49E-46 37.78496 42.38135 37.78496 42.38135 2269 31 Weight -0.00517 0.000307 -16.843 1.67E-26 -0.00578 -0.00456 -0.00578 -0.00456 5674 15 3402 20 4029 19 3996 16 3242 23 2434 31 2575 29 2960 27 3618 15 4054 19 3192 24 3305 23 3605 19 4240 15 3933 18 3633 19 3790 17 3477 20 3258 21 4685 17 2776 25 2615 24 3186 21 5137 13 3461 21 4233 16 4178 18 4702 17 3713 22 5794 14 2306 28 3194 26 3428 22 4894 12 4751 17 2605 29 3296 25 5267 13 2789 25 3570 19 4011 18 2363 27 4398 15 2806 25 2127 36 2665 27 3419 24 3427 24 3280 25 5765 13 3465 24 2295 30 3038 22 3070 25 4711 17 3230 24 3528 21 4667 16