(15 points) In order to adjust for gender, height and age, multiple regression was used to build a second model. The output from this multivariate model is below. > summary (Im(Cholesterol~., temp) ) Call: Im(formula = Cholesterol ~ ., data = temp) Residuals : Min 10 Median 30 Max -56.60 -13. 15 -2.21 9.92 111.31 Coefficients: Estimate Std. Error t value Pr(> |t| ) (Intercept) -69.740 62. 008 -1.12 0.26355 Age 1. 651 0.379 4.36 3.3e-05 *** Gender -7.975 7.934 -1.01 0.31739 Weight -0. 318 0. 119 -2.68 0.00858 * * Height 3.168 0. 886 3.58 0.00055 * * * Signif. codes: 8 * * *' 0 . 001 (**' 0.01 *' 0.05 .' 0.1 5 ' 1 Residual standard error: 28 on 95 degrees of freedom Multiple R-squared 0.271, Adjusted R-squared: 0.24 F-statistic: 8.81 on 4 and 95 DF, p-value: 4.27e-06