1. Write the estimated equations for both models (the equation of the line for model1 and model2. (50 points) 2. Does the variable "cyl" explain well the variability in "mpg"? explain why. (25points) 3. Does the variable "hp" explain well the variability in "mpg"? explain why. (25 points) Call: 1m(formula = mpg ~ cyl, data = mtcars) Residuals: Min 1Q Median 3Q Max -4.9814 -2.1185 0.2217 1.0717 7.5186 Coefficients: Estimate Std. Error t value Pr(>It!) (Intercept) 37.8846 2.0738 18.27 < 2e-16 *** cyl -2.8758 0.3224 -8.92 6.11e-10 *** Signif. codes: ***** 0.001 *** 0.01 * 0.05. 0.1'' 1 Residual standard error: 3.206 on 30 degrees of freedom Multiple R-squared: 0.7262, Adjusted R-squared: 0.7171 F-statistic: 79.56 on 1 and 30 DF, p-value: 6.113e-10 lm(formula mpg cyl + hp, data = mtcars) Residuals: Min 1Q Median 3Q Max 7.2934 -4.4948 -2.4901 -0.1828 1.9777 Coefficients: (Intercept) 36.90833 Estimate Std. Error t value Pr(>It!) 2.19080 16.847 < 2e-16 cyl hp -2.26469 -0.01912 0.57589 -3.933 0.00048 0.01500 -1.275 0.21253 Signif. codes: 0 0.001 0.01 0.05. 0.1'1 Residual standard error: 3.173 on 29 degrees of freedom Multiple R-squared: 0.7407, Adjusted R-squared: 0.7228 F-statistic: 41.42 on 2 and 29 DF, p-value: 3.162e-09