The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi'gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY {(highway fuel consumption in mi/gal). The equation CITY = - 3.11 + 0.815HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2740 Ib, it has an engine displacement of 2.3 L, and its highway fuel consumption is 41 mifgal. What is the best predicted value of the city fuel consumption? s that predicted value likely to be a good estimate? |s that predictad value likely to be very accurate? EH Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is v (Type an integer or a decimal. Do not round.) The predicted value | likely to be a good estimate and | likely to be very accurate because v \fGiven the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r= 0.543, n =25 O A. Critical values: r = 10.487, significant linear correlation O B. Critical values: / = 1 0.396, no significant linear correlation O C. Critical values: / = 10.487, no significant linear correlation O D. Critical values: / = 10.396, significant linear correlation