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This test: 100 point(s) possible = Test: Week 2 Test (10.1-10.5) Test: Week 2Test (10.1-10.5) Question 20 of 20 This test: 100 point(s) possible This

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This test: 100 point(s) possible = Test: Week 2 Test (10.1-10.5)

Test: Week 2Test (10.1-10.5) Question 20 of 20 This test: 100 point(s) possible This question: 5 point(s) possible Submit test The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 27 cars and their highway fuel consumption amounts (in mi/gl). Along with the paired sample data, Minitab was also given a car weight of 3000 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 27 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. The linear correlation coefficient is (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? O Yes O No Statcrunch Minitab output The regression equation is Highway = 50.0 - 0.00590 Weight Predictor Constant Coef 50.016 SE Coef 2.736 0.0007631 R -sq = 65.0% R- Sq(adj) = 62.1% 17.13 - 7.53 P 0.000 0.000 Weight -0.0059024 s = 2.26957 Predicted Values for New Observations New Obs Fit 32.309 SE Fit 0.481 (31.289, 33.329) 95% Pl (27.716, 36.902) Values of Predictors for New Observations New Obs 1 Weight 3000

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