### Regression Analysis TableThe table below summarizes the results of a regression analysis performed to understand the relationship between various predictor variables and a dependent variable, likely related to city mileage (CITY).#### Table: Regression Analysis Summary| Predictor (x) Variables | P-Value | R² | Adjusted R² | Regression Equation ||-------------------------|---------|------|-------------|----------------------------------------------|| WT/DISP/HWY | 0.000 | 0.943| 0.933 | CITY = 6.89 - 0.00127WT - 0.255DISP + 0.654HWY || WT/DISP | 0.000 | 0.747| 0.719 | CITY = 37.7 - 0.00163WT - 1.25DISP || WT/HWY | 0.000 | 0.943| 0.937 | CITY = 6.66 - 0.00163WT + 0.665HWY || DISP/HWY | 0.000 | 0.934| 0.927 | CITY = 1.86 - 0.629DISP + 0.703HWY || WT | 0.000 | 0.711| 0.696 | CITY = 42.1 - 0.00602WT || DISP | 0.000 | 0.658| 0.640 | CITY = 28.9 - 2.98DISP || HWY | 0.000 | 0.924| 0.920 | CITY = - 3.16 + 0.821HWY |#### Key Metrics:- **Predictor (x) Variables**: These are the independent variables in the regression model.- **P-Value**: This indicates the significance of the predictors in the model. A P-Value of 0.000 suggests that the predictors are highly significant.- **R² (R-squared)**: This is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination.- **Adjusted R²**: This is the R-squared adjusted for the number of predictors in the model. It adjusts ### 10.4.9The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). If only one predictor (x) variable is used to predict the city fuel consumption, which single variable is best? Why?[Table Icon] Click the icon to view the table of regression equations.The best variable is [Dropdown Menu] because it has the best combination of [Dropdown Menu] P-value, [Blank Field], and [Dropdown Menu] adjusted R², [Blank Field].(Type integers or decimals. Do not round.)

Given, The accompanying table shows results from regression performed on data from a random sample…

The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). If only one predictor (x) variable is used predict the city fuel consumption, which single variable is best? Why? E Click the icon to view the table regression equations. The best variable is because it has the best combination of P-value,. and V adjusted R2, N (Type integers or decimals. Do not round.)

The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). If only one predictor (x) variable is used predict the city fuel consumption, which single variable is best? Why? E Click the icon to view the table regression equations. The best variable is because it has the best combination of P-value,. and V adjusted R2, N (Type integers or decimals. Do not round.)

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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