Question Completion Status: QUESTION 6 A multiple linear regression is fitted to a data set and the following output has been returned in R. What is the correct conclusion? model. final - 1m (Longnose - Acerage + Maxdepth + NO3, data-Data) summary (model.final) Estimate Std. Error t value Pr (>\t\2 (Intercept) -2.383e+01 1.527e+01 -1.560 0.12367 Acer age Maxdepth NO3 1.988e-03 3.366e-01 8.673e+00 6.742e-04 2.948 0.00446 ** 1.776e-01 1.896 0.06253 2.773e+00 3.127 0.00265 ** Multiple R-squared: 0.2798, Adjusted R-squared: F-statistic: 8.289 on 3 and 64 DF, Text Version of R Output 0.2461 p-value: 9.717e-05 The t-test, F-test, and adjusted R-square are giving the same results that the model does not need any improvement. Even though one of the predictors is not significant, the entire regression model is significant. The entire model is not statistically significant because the r-square is small. Two of the predictors are significant but the entire model is not because all the predictors are not significant. 10 poin Click Save and Submit to save and submit. Click Save All Answers to save all answers. 30 tutor questions textbook solutions for more acces Blackboard New Tab X 14 O model, final - 1m(Longnose " Acerage + Paxdepth + 103, data-Data) Summary(model.final) Estimate (Intercept) -2.383491 Acerage 1.988e-03 Maxdepth 3.366e-91 NO3 8.673e+00 Std. Error t value 1.527e+01 -1.560 6.742e-04 2.948 1.775e-01 1.896 2.773e+00 3.127 Multiple R-squared: 0.2798, Adjusted R-sqaured: 0.2461 Pr(>iti) 8.12367 e.00446 ** 0.06253 0.00265 ** F-statistic: 8.289 on 3 and 64 DF, p-value: 9.717e-05