1. The statistical software R contains many in-built datasets. One such dataset is the mtcarsdataset. A certain Prof. Kumar ran a linear regression and obtained the following results:
2. 

Call: Im(formula = mtcars$hp ~ mtcarsimpg + mtcars$cyl + mtcars$wt + mtcars$disp) Residuals : Min 10 Median 3Q Max -59.061 -20.648 -3.756 16.950 129.436 Coefficients : Estimate Std. Error t value Pr(>Itl) (Intercept) 178.0516 120.6894 1.475 0. 152 mtcars$mpg -4.6620 2.7572 -1. 691 0. 102 mtcars$cyl 15.6155 10.1329 1.541 0.135 mtcars$wt -27.5747 18.1871 -1.516 0. 141 mtcars$disp 0.2357 0. 1740 1.355 0.187 Residual standard error: 37.85 on 27 degrees of freedom Multiple R-squared: 0.7345, Adjusted R-squared: 0.6952 F-statistic: 18.67 on 4 and 27 DF, p-value: 1.831e-07