om/courses/337235/quizzes/secured#lockdown We could use this model to predict the release rate for a tablet with surface area to volume ratio of 1.8 Since O is not in the range of the given surface area to volume ratio (x) values, we should not interpret the estimate of Beta0 for this problem The regression line is estimated to be: release rate = 9.430 + 24.099 * surface area to volume ratio (x) Question 18 3 pts Which one of the following statements is NOT an assumption of the simple linear regression model fitted in Question 16? O The regression residuals are independent The regression residuals are normally distributed O Regression residuals indicate significant correlation between the dependent and the independent variables The regression residuals have constant variance Question 19 3 pts As we know, when a simple linear regress model is found to be overall useful, then we can use it for estimation and prediction of certain values such as the point estimate, the Confidence Interval, and earchm/courses/337235/quizzes/secured#lockdown Question 16 4 pts The effect of tablet surface area and volume on the rate at which a drug is released in a controlled- release dosage is of interest to chemical companies. In one study, six similarly shaped tablets were prepared with different weights and thicknesses, and the ratio of surface area to volume was measured for each. Using a dissolution apparatus, each tablet was placed in 900 milliliters of deionized water, and the diffusional drug release rate (percentage of drug released divided by the square root of time) was determined. The following simple linear regression model was fitted : release rate (y) = Bo + 31 surface area to volume ratio (x) + & Using RStudio, the following scatter plot and regression output were generated: FBes Plots Packages Help Viewer Presentation ReleaseRate 0.4 0.6 0.8 1.0 1.2 earch O O Ncourses/337235/quizzes/secured#lockdown Response: ReleaseRate of Sum Sq Mean Sq F value Pr ( >F ) SurfAreaTovolume 1 323. 53 323. 53 162, 28 0. 0002188 Residuals 4 7. 97 1. 99 Signif. codes : 0 ' * * ' 0. 001 ' ' 0. 01 9 0. 05 . . ' 0.1 : ' 1 Find the 99% Confidence Interval for Beta1. What does this confidence interval indicate about the overall usefulness of the regression model? O The 99% Confidence Interval for Beta 1 is from 2.713 to 16.147 . Since this confidence interval is all positive and does not include 0, we can conclude that at the 99% confidence level the slope is not zero and the regression model is useful The 99% Confidence Interval for Beta 1 is from -5.051 to 23.911 . While this confidence interval includes 0, we can clearly see it from the scatter plot above that the slope is positive, so the regression model is useful O The 99% Confidence Interval for Beta 1 is from -5.051 to 23.911 . Since this confidence interval includes 0, we can conclude that at the 99% confidence level the slope could be positive, negative or zero, so the regression model is not useful O The 99% Confidence Interval for Beta 1 is from 15.388 to 32.810 . Since this confidence interval is all positive and does not include 0, we can conclude that at the 99% confidence level the slope is not zero and the regression model is useful Question 17 3 pts ased on the regression output presented in Question 16, which statement is NOT correct? arch NSurfArea ToVolume Console Terminal Background Jobs x R 4.2.1 . F:/Teaching/BA 2551 Fall 2022/Lectures/Lecture 10/ > model summary (model) call : Im(formula = ReleaseRate - SurfAreaTovolume) Residuals : 1 5 6 -0. 7584 2. 0860 -0. 2992 -0. 6844 0. 9304 -1. 2745 Coefficients : Estimate Std. Error t value pr (>It|) (Intercept) 9. 430 1. 459 6. 465 0. 002949 SurfAreaToVolume 24. 099 1. 892 12. 739 0. 000219 * *x Signif. codes: 0 ' * * ' 0. 001 . * ' 0. 01 '#' 0. 05 '. ' 0.1 . . Residual standard error: 1. 412 on 4 degrees of freedom Multiple R-squared: 0. 9759, Adjusted R-squared: 0. 9699 F-statistic: 162. 3 on 1 and 4 DF, p-value: 0. 0002188 > ##Create the ANOVA portion of the analysis for the linear model > anova (model) Analysis of variance Table Response: ReleaseRate of Sum Sq Mean Sq F value Pr (>F) SurfAreaToVolume 1 323. 53 323.53 162. 28 0. 0002188 * * * Residuals 7. 97 1. 99 Signif. codes: 0 0. 001 '* *' 0. 01 '*' 0. 05 ..' 0.1 . ' 1 Find the 99% Confidence Interval for Beta1. What does this confidence interval indicate about t overall usefulness of the regression model? earch Nom/courses/337235/quizzes/secured#lockdown The 99% Confidence Interval for Beta 1 is from -5.051 to 23.911 . Since this confidence interval includes O, we can conclude that at the 99% confidence level the slope could be positive, negative or zero, so the regression model is not useful The 99% Confidence Interval for Beta 1 is from 15.388 to 32.810 . Since this confidence interval is all positive and does not include 0, we can conclude that at the 99% confidence level the slope is not zero and the regression model is useful Question 17 3 pts Based on the regression output presented in Question 16, which statement is NOT correct? O About 97.59 % of the variation in the mean release rate is explained by this simple linear regression model using surface area to volume ratio as predictor We could use this model to predict the release rate for a tablet with surface area to volume ratio of 1.8 Since 0 is not in the range of the given surface area to volume ratio (x) values, we should not interpret the estimate of Beta0 for this problem O The regression line is estimated to be: release rate = 9.430 + 24.099 * surface area to volume ratio (x) Question 18 3 pts Which one of the following statements is NOT an assumption of the simple linear regression model Search N