Question

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 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 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. The linear correlation coefficient is Minitab output (Round to three decimal places as needed.) The regression equation is Highway = 50.5-0.00501 Weight Predictor Coef Constant 50.465 Weight -0.0050096 SE Coef 2.883 0.0007962 T 17.15 -7.79 P 0.000 0.000 S=227663 R-Sq=64.4% R-Saadi)-61.7% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 1 35,436 0.499 (34.435, 36437) 95% PI (30.846, 40.027) Values of Predictors for New Observations New Obs Weight 1 3000

Is there sufficient evidence to support a claim of linear correlation?

Yes or No

Answer 1

Answer:-

Testing To test, Hospe o Vis HI: Pto stept steps Test statistic, t = r 5n-z Si-ra 50.644 = 0.802 {": from minitab output R² 0.644 n29 ta 0.802527 0.802² &า 6.977 2052 steps tecitical = tn 2, 0/2 tale as 0.05 tertical dif = n2=27 steny decision: Here tx treitical, so we Refect Ho at 5% level of significance. steps Conclusion: There Yes, there is sufficient sufficient evidence to support the claim of linear correlation, H

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