Please answer the following using r code provided

The quality of Pinot Noir wine is thought to be related to the properties of clarity, aroma, body, flavor, and oakiness. Data for 38 wines are given in hmw5-probl (a) Fit a multiple linear regression model relating wine quality to these regressors. (b) Construct the ANOVA table. (c) Test for the significance of the regression in a 0.05 significance level. What conclu sions can you draw? a 0.05 significance level. Discuss your findings. all of the other regressors are included? Perform this hypothesis test using 0.05 significance (d) Use the t tests to assess the individual contribution of each regressor to the model in (e) What is the contribution of the set of clarity and aroma to the model, given that level. (f) Find a 95% confidence interval for the regression coefficient for flavor. (8) Calculate R2 and Rad for this model. Compare these values to the R2 d for the regression model relating wine quality to aroma and flavor. Discuss your results. # quality is y 2 # clarity is x1, aroma is x2, body is x3, flavor is x4, oakiness is x5 15:1 Top Leve) Console Terminal > #tit the regression > model1m(y x1+x2+x3+x4+x5) > summary (model) Call: 1m(formula y~xl+ x2 + x3 x4 x5) Residuals: -2.85552-0.57448 -0.07092 0.67275 1.68093 Coefficients (Intercept) .9969 Min 1Q Median 3Q Max Estimate Std. Error t value Pr(Itl 2. 3395 0.4826 0.2732 1.1683 -0.6840 2.2318 1.791 0.082775. 1.73481.349 0.186958 0.2724 1.771 0.086058 . 0.3326 0.821 0.417503 0.3045 3.837 0.000552 0.27122.522 0.016833 signif. codes: 0 , 0.001 **, 0.01 *, 0.05 , 0.1 , 1 Residual standard error 1.163 on 32 degrees of freedom Multiple R-squared: 0.7206,Adjusted R-squared: 0.6769 F-statistic: 16.51 on 5 and 32 DF, p-value: 4.703e-08 > anova(mode) Analysis of Variance Table Response: y Sq F value Pr>F) 1 0.125 0.125 0.0926 0.7628120 Df Sum Mean 1 77.353 77.353 57.2351 1.286e-08 *s 1 6.414 6.414 4.7461 0.0368417 1 19.050 19.050 14.0953 0.0006946 1 8.598 8.598 6. 3616 0.0168327 Residuals 32 43.248 1.352 Signif. codes: 0 '*0.0010.01 0.05 0. '1 mode1