Question

Find the regression equation, leting the first variable be the predictor) variable. Using the listed lemoncs rate for a year in which there are 400 metric tons of lemon imports is the prediction worthwhile? ia where lemon imports are in cons and the rates are per 100.000 people, sed the best pri ces Lemon Imports 233 263 Crash Fatality Rate 16.1 159 356 156 460 155 5245 151 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 tality rate for a year in which there are 400 metric tons of lemon imports is t es per 100.000 population (Round to one decimal place as needed.) is the prediction worthwhile? O A. Since the sample size is smal, the prediction is not appropriate O B. Since there appears to be an outler, the prediction is not appropriat OC. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make me OD. Since all of the requirements for finding the equation of the regression in are met, the prediction is worthwhile

Answer 1

X X? Y? X, Y 233 16.1 54289 259.21 3751.3 263 15.9 69169 252.81 41817 356 15.6 126736 243.36 55536 460 15,5 211600 240.25 7130 524 15.1 274576 228.01 7912.4 Sum - 1836 78.2 736370 1223,64 28529 The sum of squares obtained from the table above are: 198xx = x -+ (2x) = 738370 – $ (1830) 62190.8 Sky - Šn-1 (3) = 1223.6 – (70.23 = 0.592 $$xy = ¿xx -- (2x) () = 28629 - (1836) (78.2) = -186.04 The slope and y-intercept coefficients are computed using the following formulas: @ SSXY = SSXX -186.04 62190.8 = -0.003 Bo = Y - @1 x = 15.64 - -0.003 x 367.2 = 16.7385 Therefore, the regression equation is: Y = 16.7385 -0.003X Now that we have the regression equation, we can compute the predicted value for X = 400, by simply plugging in the value of X = 400 in the regression equation found above: û = 16.7385 – 0.003 x 400 = 15.5419 Since common sense suggest that there should not be much relationship between this two variables prediction does not make much sense.