Now we have seen the output of a simple linear regression in R. Use the output of linear regression analysis of the student weight and height data you did on worksheet 3. Explain the main parts of output. ( the residuals, R -sqaured, the coefficients table, and anova table) lm.fit lm (wt-ht, data WH) summary (1m.fit) ## Call: ## lm(formula = wt -ht, data = WH) ## Residuals: 1Q Median ##-13.2339-4.0804-0.0963 4.6445 14.2158 Min Max ## Coefficients: Estimate Std. Error t value Pr>ltI) 8e-04 51.0320-5.223 ##(Intercept)-266.5344 ## ht 6.1376 0.7353 8.347 3.21e-05* ## Signif . codes : 0 ' ' 0.001 '**' 0.01 .*. 0.05 ',' 0.1 ' ' 1 ## Residual standard error: 8.641 on 8 degrees of freedom ## Multiple R-squared: 0.897, Adjusted R-squared: 0.8841 ## F-statistic: 69.67 on 1 and 8 DF, p-value: 3.214e-05 anova (1mfit) ## Analysis of Variance Table ## Response: wt Df Sum Sq Mean Sq F value PrF) 1 5202.2 5202.2 69.666 3.214e-05 ## ht ##Residuals 8597.4 74.7