Values of predictors for the new observation Obs 1 weight 4500

The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 29 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 29 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. Minitab output The linear correlation coefficient is The regression equation is (Round to three decimal places as needed.) Highway = 50.8 - 0.00503 Weight Is there sufficient evidence to support a claim of linear correlation? Predictor Coef SE Coef T P Constant 50.768 2.721 17.09 0.000 O No Weight - 0.0050299 0.0007669 -7.01 0.000 O Yes S =2.25788 R - Sq=65.8% R- Sq(adj) =63.2% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 28.133 0.475 (27.128, 29.138) (23.535, 32.731) Statcrunch Values of Predictors for New Observations New Print Done