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 500 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16.1 16 234 260 360 15.7 464 15.5 547 15.1 Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 500 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 there appears to be an outlier, the prediction is not appropriate. O B. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile. OC. Since the sample size is small, the prediction is not appropriate. OD. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense.

Given, The data contains 5 observations in that lemon imports is a independent variable and crash fatality rate is a dependent/response variable. Sr no x y x2 y2 xy 1 234 16.1 54756 259.21 3767.4 2 260 16 67600 256 4160 3 360 15.7 129600 246.49 5652 4 464 15.5 215296 240.25 7192 5 547 15.1 299209 228.01 8259.7 Total 1865 78.4 766461 1229.96 29031.1Formula for regression coefficients is, β=n∑xy-(∑x)(∑y)n∑x2-(∑x)2 =5×29031.1 - 1865×78.45×766461 - 18652 =145155.5 -146216 3832305 - 3478225 =-1060.5354080 β=-0.003 α=y¯ - βx¯ =∑yn -β∑xn =78.45-(-0.003)18655 =15.68+0.003×373 =15.68 + 1.1172 α=16.7972 Hence, The regression equation is, y^=16.7972 - 0.003xThe predicted value of y^ when x = 500 is, y^=16.7972 - 0.003×500 =16.7972 - 1.4975 y^=15.2996 Hence, since the sample size is small, prediction is not appropriate.