Please help me better understand this problem. Researchers want to determine if heavier cars use more gasoline? To answer this question, a researcher randomly selected 15 cars. He collected their weight (in hundreds of pounds) and the mileage (MPG) for each car. From a scatterplot made with the data, a linear model seemed appropriate and the following output was obtained in photo below.Question: Determine the proportion of the variation in mileage is accounted for by the linear relationship with the weight of the car and also determine the estimate of the regression standard deviation. The following output was obtained from SAS:A table displays the R-Square value and Root Mean Square Error (MSE):- **R-Square**: 0.438- **Root MSE**: 6.78Another table provides the results of a regression analysis, including the parameter estimates, standard error, t-value, and p-value:| Parameter | Estimate | Standard Error | t Value | Pr > |t| ||-----------|----------|----------------|---------|------|| Intercept | 40.439 | 6.275 | 6.445 | 0.0000 || WEIGHT | -0.521 | 0.164 | -3.182 | 0.0072 |This output suggests that the model explains approximately 43.8% of the variance in the response variable. The intercept is 40.439, and the coefficient for the WEIGHT variable is -0.521, indicating a negative relationship. Both have statistically significant p-values.

Answered: Researchers want to determine if…

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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Please help me better understand this problem.

Researchers want to determine if heavier cars use more gasoline? To answer this question, a researcher randomly selected 15 cars. He collected their weight (in hundreds of pounds) and the mileage (MPG) for each car. From a scatterplot made with the data, a linear model seemed appropriate and the following output was obtained in photo below.

Question: Determine the proportion of the variation in mileage is accounted for by the linear relationship with the weight of the car and also determine the estimate of the regression standard deviation.