Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports. Is the prediction worthwhile? Find the equation of the regression line (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports is fatalities per 100,000 population (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense O B. Since there appears to be an outlier, the prediction is not appropriate. C. Since the sample size is small, the prediction is not appropriate D. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile

Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a which there are 400 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 231 268 351 460 540 0 Crash Fatality Rate 16 15.8 15.5 15.4 149 Find the equation of the regression line. * = ] + 1 x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed ) Is the prediction worthwhile? O A. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense O B. Since there appears to be an outlier, the prediction is not appropriate. O C. Since the sample size is small, the prediction is not appropriate. O D. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile