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SU bes and Car Data Weight Highway Fuel Consumption 36 38 41 33 42 31 40 2844 3109 2870 3095 2915 2985 2563 3009 2798 2468 2598 2558 3452 3514 3344 3146 2545 Print 37 35 40 38 37 36 32 39 38 32 Done - X .75 of 1 data set, one ge he best predicted va

SU bes and Car Data Weight Highway Fuel Consumption 36 38 41 33 42 31 40 2844 3109 2870 3095 2915 2985 2563 3009 2798 2468 2598 2558 3452 3514 3344 3146 2545 Print 37 35 40 38 37 36 32 39 38 32 Done - X .75 of 1 data set, one ge he best predicted va

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Car Data Overview** The table below presents information on various cars, showcasing their weight (in pounds) and corresponding highway fuel consumption (measured in miles per gallon). This data can be useful for understanding the relationship between a car's weight and its fuel efficiency on highways. | Weight (lbs) | Highway Fuel Consumption (mpg) | |--------------|---------------------------------| | 2844 | 36 | | 3109 | 38 | | 2870 | 41 | | 3095 | 33 | | 2915 | 42 | | 2985 | 31 | | 2563 | 40 | | 3009 | 37 | | 2798 | 35 | | 2468 | 40 | | 2598 | 38 | | 2558 | 37 | | 3452 | 36 | | 3514 | 32 | | 3344 | 39 | | 3146 | 38 | | 2545 | 32 | This dataset facilitates analysis of how vehicle weight affects fuel consumption on highways, potentially aiding in decisions related to environmental impact and cost efficiency of operating different car models.
Transcribed Image Text:**Car Data Overview** The table below presents information on various cars, showcasing their weight (in pounds) and corresponding highway fuel consumption (measured in miles per gallon). This data can be useful for understanding the relationship between a car's weight and its fuel efficiency on highways. | Weight (lbs) | Highway Fuel Consumption (mpg) | |--------------|---------------------------------| | 2844 | 36 | | 3109 | 38 | | 2870 | 41 | | 3095 | 33 | | 2915 | 42 | | 2985 | 31 | | 2563 | 40 | | 3009 | 37 | | 2798 | 35 | | 2468 | 40 | | 2598 | 38 | | 2558 | 37 | | 3452 | 36 | | 3514 | 32 | | 3344 | 39 | | 3146 | 38 | | 2545 | 32 | This dataset facilitates analysis of how vehicle weight affects fuel consumption on highways, potentially aiding in decisions related to environmental impact and cost efficiency of operating different car models.
**Regression Analysis of Car Weights and Highway Fuel Consumption** **Problem Statement:** Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one obtains the following regression equation: \[ \hat{y} = 58.9 - 0.00749x \] where \( x \) represents weight. **Tasks:** **a. Determining the Slope and Intercept:** - Select the correct option: - A: The slope is 58.9 and the y-intercept is -0.00749. - B: The slope is -0.00749 and the y-intercept is 58.9. - C: The slope is -58.9 and the y-intercept is 0.00749. - D: **The slope is -0.00749 and the y-intercept is 58.9.** **b. Predictor Variable Identification:** - What is the predictor variable? - A: The predictor variable is highway fuel consumption, which is represented by \( x \). - B: The predictor variable is highway fuel consumption, which is represented by \( y \). - C: **The predictor variable is weight, which is represented by \( x \).** - D: The predictor variable is weight, which is represented by \( y \). **c. Prediction Based on Linear Correlation:** - Assuming a significant linear correlation between weight and highway fuel consumption, calculate the best predicted value for a car that weighs 2994 lb. \[ \text{The best predicted value of highway fuel consumption of a car that weighs 2994 lb is } \_\_\_ \text{ mi/gal.} \] *Note: Round your answer to one decimal place as necessary.*
Transcribed Image Text:**Regression Analysis of Car Weights and Highway Fuel Consumption** **Problem Statement:** Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one obtains the following regression equation: \[ \hat{y} = 58.9 - 0.00749x \] where \( x \) represents weight. **Tasks:** **a. Determining the Slope and Intercept:** - Select the correct option: - A: The slope is 58.9 and the y-intercept is -0.00749. - B: The slope is -0.00749 and the y-intercept is 58.9. - C: The slope is -58.9 and the y-intercept is 0.00749. - D: **The slope is -0.00749 and the y-intercept is 58.9.** **b. Predictor Variable Identification:** - What is the predictor variable? - A: The predictor variable is highway fuel consumption, which is represented by \( x \). - B: The predictor variable is highway fuel consumption, which is represented by \( y \). - C: **The predictor variable is weight, which is represented by \( x \).** - D: The predictor variable is weight, which is represented by \( y \). **c. Prediction Based on Linear Correlation:** - Assuming a significant linear correlation between weight and highway fuel consumption, calculate the best predicted value for a car that weighs 2994 lb. \[ \text{The best predicted value of highway fuel consumption of a car that weighs 2994 lb is } \_\_\_ \text{ mi/gal.} \] *Note: Round your answer to one decimal place as necessary.*
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