Model Summary - mpg
Model	R	R	Adjusted R	RMSE
1		0.000		0.000		0.000		4.294
2		0.818		0.670		0.668		2.476
3		0.840		0.705		0.701		2.348
4		0.857		0.734		0.728		2.238
5		0.865		0.749		0.742		2.180

ANOVA
Model		Sum of Squares	df	Mean Square	F	p
2		Regression		1877.288		1		1877.288		306.273		<.001
		Residual		925.549		151		6.129
		Total		2802.837		152
3		Regression		1975.593		2		987.796		179.112		<.001
		Residual		827.244		150		5.515
		Total		2802.837		152
4		Regression		2056.374		3		685.458		136.823		<.001
		Residual		746.463		149		5.010
		Total		2802.837		152
5		Regression		2099.452		4		524.863		110.437		<.001
		Residual		703.385		148		4.753
		Total		2802.837		152
Note.The intercept model is omitted, as no meaningful information can be shown.

Coefficients
Model		Unstandardized	Standard Error	Standardized	t	p
1		(Intercept)		23.856		0.347				68.718		<.001
2		(Intercept)		42.558		1.087				39.144		<.001
		curb_wgt		-5.538		0.316		-0.818		-17.501		<.001
3		(Intercept)		42.516		1.031				41.224		<.001
		curb_wgt		-3.358		0.597		-0.496		-5.622		<.001
		fuel_cap		-0.408		0.097		-0.373		-4.222		<.001
4		(Intercept)		41.242		1.033				39.927		<.001
		curb_wgt		-2.064		0.654		-0.305		-3.154		0.002
		fuel_cap		-0.398		0.092		-0.364		-4.320		<.001
		engine_s		-1.074		0.267		-0.262		-4.016		<.001
5		(Intercept)		33.804		2.667				12.673		<.001
		curb_wgt		-2.534		0.656		-0.374		-3.862		<.001
		fuel_cap		-0.415		0.090		-0.379		-4.619		<.001
		engine_s		-1.172		0.263		-0.286		-4.464		<.001
		length		0.052		0.017		0.161		3.011		0.003
Note.The following covariates were considered but not included: horsepow, wheelbas, width.

Based on the above results answer the following questions:

1. Determine the best fitted regression model.
2. Write the equation of the regression model (best -fit model) and interpret all the Beta coefficients.
3. Interpret the ANOVA for regression fit.
4. Determine and interpret the coefficient of determination r2.
5. What can we conclude about the relationship of the dependent and predictor variables?