The output below present the weight in metric tons of lemon imported in the US car crash fatality rates per 100,000 people.

SUMMARY OUTPUT 15.6 Regression Statistics 15.4 Multiple R 0.939894457 R Square 0.88340159 15.2 Adjusted R Square 0.860081907 is Standard Error 0.125395887 Observations 14.8 100 200 300 400 SOO GOO ANOVA SS MS F Significance F Regression 1 0.595665072 0.595665 37.88223 0.001646686 Residual 0.078620542 0.015724 Total 0.674285714 Coefficients Standard Error tStat P.value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 16.51743501 0.18315002 90.18528 3.18E-09 16.04663289 16.988237 16.0466329 16.9882371 Lemon Imports 0.002918088 0.000474112 -6.15485 0.001647 -0.00413683 -0.0016993 -0.0041368 -0.00169935 7. What is the formula needed to predict U.S. car crash fatality rate if there are 340 metric tons of import lemons from Mexico? (a) y - 16.52(340) - 0.003 (b) y = 16.52 - 0.003(340) cy - 16.52(340) - 0.003 (d) y = 16.52 - 0.003(340) State the correlation value that best represents the plot presented. (a) 0.94 (b) 0.88 (c) -0.88 (d) -0.94 Interpret the slope of the line. (a) For a 1% increase in U.S. car crash fatality rate, imported lemons will, on average, decrease by 0.003 m (b) For a 1% increase in U.S. car crash fatality rate, imported lemons will, on average, increase by 16.5 me (c) For a 1 metric ton increase in imported lemons, U.S. car crash fatality rate will, on average, decrease d) For a 1 metric ton increase in imported lemons, U.S. car crash fatality rate will, on average, increase (e) We should not interpret the slope in this problem. Interpret the y-intercept of the line. (a) On average, when z = 0, there are 16.5 metric tons of imported lemons. (b) On average, when r = 0, there are -0.003 metric tons of imported lemons. (c) On average, when r = 0, the U.S. car crash fatality rate is 16.5%- (d) We should interpret y-intercept but none of the above are correct. e) We should not interpret the y-intercept in this