Homework Help is Here – Start Your Trial Now!
Math
Statistics
The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 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 31 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? E Click the icon to view the Minitab display. - X Minitab output The linear correlation coefficient is. The regression equation is Highway = 50.5 - 0.00594 Weight (Round to three decimal places as needed.) Predictor Constant Weight Coef SE Coef 50.544 2.978 17.85 0.000 -0.0059351 0.0007513 -7.28 0.000 S=2.10089 R-Sq = 63.2% R-Sq(adj) = 60.6% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 26.804 0.524 (25.789, 27.819) (22.208, 31.400) Values of Predictors for New Observations New Obs Weight 1 4000

The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 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 31 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? E Click the icon to view the Minitab display. - X Minitab output The linear correlation coefficient is. The regression equation is Highway = 50.5 - 0.00594 Weight (Round to three decimal places as needed.) Predictor Constant Weight Coef SE Coef 50.544 2.978 17.85 0.000 -0.0059351 0.0007513 -7.28 0.000 S=2.10089 R-Sq = 63.2% R-Sq(adj) = 60.6% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 26.804 0.524 (25.789, 27.819) (22.208, 31.400) Values of Predictors for New Observations New Obs Weight 1 4000

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 7E
See similar textbooks
icon
Related questions
Question
The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 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 31 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.) = 50.5 - 0.00594 Weight Predictor Coef SE Coef P Constant 50.544 2.978 17.85 0.000 Weight - 0.0059351 0.0007513 - 7.28 0.000 S= 2.10089 R-Sq = 63.2% R- Sq(adj) = 60.6% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 26.804 0.524 (25.789, 27.819) (22.208, 31.400) Values of Predictors for New Observations New Obs Weight 1 4000
Transcribed Image Text:The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 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 31 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.) = 50.5 - 0.00594 Weight Predictor Coef SE Coef P Constant 50.544 2.978 17.85 0.000 Weight - 0.0059351 0.0007513 - 7.28 0.000 S= 2.10089 R-Sq = 63.2% R- Sq(adj) = 60.6% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 26.804 0.524 (25.789, 27.819) (22.208, 31.400) Values of Predictors for New Observations New Obs Weight 1 4000
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps with 2 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
Calculus For The Life Sciences
Calculus For The Life Sciences
Calculus
ISBN:
9780321964038
Author:
GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:
Pearson Addison Wesley,
Glencoe Algebra 1, Student Edition, 9780079039897…
Glencoe Algebra 1, Student Edition, 9780079039897…
Algebra
ISBN:
9780079039897
Author:
Carter
Publisher:
McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Algebra
ISBN:
9781680331141
Author:
HOUGHTON MIFFLIN HARCOURT
Publisher:
Houghton Mifflin Harcourt
SEE MORE TEXTBOOKS