Question

The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 28 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 28 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. i Minitab output The linear correlation coefficient is - (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? The regression equation is Highway = 50.7 -0.00534 Weight O Ο Yes Νο Predictor Constant Weight Coef 50.652 -0.0053413 SE Coef 2.742 0.0007975 17.850.000 -7.130.000 S = 2.18662 R-Sq = 66.6% R-Sq(adj)= 63.9% Predicted Values for New Observations New Obs Fit 26.616 SE Fit 0.472 95% CI (25.611, 27.621) 95% PI (22.022, 31.211) Values of Predictors for New Observations New Obs Weight 4500 Click to select your answer(s).

Answer 1

Solution:

The linear correlation coefficient is,

r = 0.816

P-value = 0.0000

Yes there is sufficient evidence to support a claim of linear correlation.