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A study of fuel economy for various automobiles plotted the fuel consumption vs. speed. A LSRL was fit to the data. Here is the residual plot from this least-squares fit. What does the pattern of the residuals tell you about the linear model? 3. D

A study of fuel economy for various automobiles plotted the fuel consumption vs. speed. A LSRL was fit to the data. Here is the residual plot from this least-squares fit. What does the pattern of the residuals tell you about the linear model? 3. D

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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A. Due to the pattern in the residual plot, the LSRL is a good fit for the data. B. Due to the non-linear nature of the residual plot, we can conclude that the LSRL is not a good fit to the data. C. Due to the pattern in the residual plot, the LSRL is not a good fit for the data. D. Since, for large values of x, the residual plot is increasing, we know that the LSRL must have a positive slope. E. The residual plot cannot be used to determine the accuracy or lack of accuracy in the model that created it.
Transcribed Image Text:A. Due to the pattern in the residual plot, the LSRL is a good fit for the data. B. Due to the non-linear nature of the residual plot, we can conclude that the LSRL is not a good fit to the data. C. Due to the pattern in the residual plot, the LSRL is not a good fit for the data. D. Since, for large values of x, the residual plot is increasing, we know that the LSRL must have a positive slope. E. The residual plot cannot be used to determine the accuracy or lack of accuracy in the model that created it.
**Question 3:** A study of fuel economy for various automobiles plotted the fuel consumption vs. speed. A Least Squares Regression Line (LSRL) was fit to the data. Here is the residual plot from this least-squares fit. What does the pattern of the residuals tell you about the linear model? **Residual Plot Description:** The plot shows residuals on the vertical axis and some measurement (likely speed, as related to fuel consumption) on the horizontal axis. The residuals (differences between observed and predicted values) are plotted as square points. The pattern demonstrates a clear curve, with residuals starting at zero, decreasing to negative, returning to zero, and then increasing to a positive trend as the independent variable increases. **Analysis:** The residual plot reveals a non-linear pattern, suggesting that the linear model is not the best fit for the data. The clear curved structure indicates that a linear model does not adequately capture the relationship between fuel consumption and speed. Instead, a non-linear model might better account for the observed variations.
Transcribed Image Text:**Question 3:** A study of fuel economy for various automobiles plotted the fuel consumption vs. speed. A Least Squares Regression Line (LSRL) was fit to the data. Here is the residual plot from this least-squares fit. What does the pattern of the residuals tell you about the linear model? **Residual Plot Description:** The plot shows residuals on the vertical axis and some measurement (likely speed, as related to fuel consumption) on the horizontal axis. The residuals (differences between observed and predicted values) are plotted as square points. The pattern demonstrates a clear curve, with residuals starting at zero, decreasing to negative, returning to zero, and then increasing to a positive trend as the independent variable increases. **Analysis:** The residual plot reveals a non-linear pattern, suggesting that the linear model is not the best fit for the data. The clear curved structure indicates that a linear model does not adequately capture the relationship between fuel consumption and speed. Instead, a non-linear model might better account for the observed variations.
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