An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B с D E Q 2615 3015 3305 3650 4250 31.8 25.8 27.4 21.9 19.4 Weight (pounds), x Miles per Gallon, y C me siope muncates the Tau petween the mean weight and the mean mies per yalivi. O D. The slope indicates the mean miles per gallon. O E. It is not appropriate to interpret the slope because it is not equal to zero. Choose the best interpretation for the y-intercept. O A. The y-intercept indicates the miles per gallon of the lightest car in the population. O B. The y-intercept indicates the mean miles for a car that weighs 0 pounds. O C. The y-intercept indicates the miles per gallon for a new car. O D. The y-intercept indicates the mean miles per gallon for a car that weighs 0 pounds. E. It is not appropriate to interpret the y-intercept because it does not make sense to talk about a car that weighs 0 pounds. (c) Predict the miles per gallon of car C and compute the residual. Is the miles per gallon of this car above average or below average for cars of this weight? The predicted value is miles per gallon. (Round to two decimal places as needed.)
An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B с D E Q 2615 3015 3305 3650 4250 31.8 25.8 27.4 21.9 19.4 Weight (pounds), x Miles per Gallon, y C me siope muncates the Tau petween the mean weight and the mean mies per yalivi. O D. The slope indicates the mean miles per gallon. O E. It is not appropriate to interpret the slope because it is not equal to zero. Choose the best interpretation for the y-intercept. O A. The y-intercept indicates the miles per gallon of the lightest car in the population. O B. The y-intercept indicates the mean miles for a car that weighs 0 pounds. O C. The y-intercept indicates the miles per gallon for a new car. O D. The y-intercept indicates the mean miles per gallon for a car that weighs 0 pounds. E. It is not appropriate to interpret the y-intercept because it does not make sense to talk about a car that weighs 0 pounds. (c) Predict the miles per gallon of car C and compute the residual. Is the miles per gallon of this car above average or below average for cars of this weight? The predicted value is miles per gallon. (Round to two decimal places as needed.)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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![### Analysis of Vehicle Weight vs. Mileage
An engineer aims to explore how the weight of a car, denoted as \( x \), impacts its gas mileage, expressed as \( y \). The dataset below summarizes the relationship between car weights and their respective miles per gallon (MPG).
#### Data Table
| Car | Weight (pounds), \( x \) | Miles per Gallon, \( y \) |
|-----|--------------------------|---------------------------|
| A | 2615 | 31.8 |
| B | 3015 | 25.8 |
| C | 3015 | 27.4 |
| D | 3650 | 21.9 |
| E | 4250 | 19.4 |
#### Interpretation of Slope and Intercept
**Best Interpretation of the Y-Intercept:**
- **E.** It is not appropriate to interpret the y-intercept because it does not make sense to talk about a car that weighs 0 pounds.
#### Prediction and Residual Calculation
**Task:**
Predict the miles per gallon for car C using linear regression and compute the residuals. Determine if the car's MPG is above or below the average for cars of this weight.
- **Predicted Value:** The predicted value for car C's MPG should be calculated using the linear regression equation derived from the data. Enter the calculated MPG below:
- The predicted value is \[ \_\_\_\_\_\_ \] miles per gallon.
*(Note: Round your predicted MPG to two decimal places as required.)*
This section is aimed at providing insights into fundamental statistical analysis in the context of automotive efficiency, which can be valuable in educational settings for students and professionals interested in engineering and data analysis.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4b16ece0-c783-4798-b8b6-3ccb9c1c7a2c%2Fbc80b12b-7228-4cf9-893c-d765c92a8270%2Fl246c66_processed.png&w=3840&q=75)
Transcribed Image Text:### Analysis of Vehicle Weight vs. Mileage
An engineer aims to explore how the weight of a car, denoted as \( x \), impacts its gas mileage, expressed as \( y \). The dataset below summarizes the relationship between car weights and their respective miles per gallon (MPG).
#### Data Table
| Car | Weight (pounds), \( x \) | Miles per Gallon, \( y \) |
|-----|--------------------------|---------------------------|
| A | 2615 | 31.8 |
| B | 3015 | 25.8 |
| C | 3015 | 27.4 |
| D | 3650 | 21.9 |
| E | 4250 | 19.4 |
#### Interpretation of Slope and Intercept
**Best Interpretation of the Y-Intercept:**
- **E.** It is not appropriate to interpret the y-intercept because it does not make sense to talk about a car that weighs 0 pounds.
#### Prediction and Residual Calculation
**Task:**
Predict the miles per gallon for car C using linear regression and compute the residuals. Determine if the car's MPG is above or below the average for cars of this weight.
- **Predicted Value:** The predicted value for car C's MPG should be calculated using the linear regression equation derived from the data. Enter the calculated MPG below:
- The predicted value is \[ \_\_\_\_\_\_ \] miles per gallon.
*(Note: Round your predicted MPG to two decimal places as required.)*
This section is aimed at providing insights into fundamental statistical analysis in the context of automotive efficiency, which can be valuable in educational settings for students and professionals interested in engineering and data analysis.
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