Question

The percentage yield from a batch reactor is believed to be affected by the purity of the feedstock. A simple linear regression model was fit to the data. The partial Minitab output of the simple linear model is given below. Regression Equation yield = 76.76 -0.0251 purity Analysis of Variance Source DF SSMS Regression 1 5.52 5.522 Error 239 9836.47 41.157 Total 240 9841.99 Residual Plots for yield Normal Pubby at Vous Fits Vargus Or Residuals Versus purity response is yiek Residual pally a) How many data points (n) were used to fit this model? b) Calculate both R2 and Se. Show your work. c) What do you conclude about the effect of feedstock purity on yield? How useful is this regression model in making predictions about yield, knowing the feedstock purity in advance? Justify your conclusions.

Answer 1

we have giren partial Minitab output of the simple linear model Regression equahon z yield z +6.76 -0.0251 purity. here yield a dependent & purity = Independent variable. Analysis of variance. source pratile mo Regression II 5.525 .522 10:1341 10.7145 Error 239 9836.47 41.157 - Total 240 | 9841.99 -

a) 241 data points ) b) 41 R = data points in) were used to fit this model, ss Regression = 5.52 = 0.00056 ) Ss Total 9841.99 SEE MSE - 541.157 = 6.4153 | o there is as purity increasest Yield value decreases No this regression model not in making about yield prediction because regression model is not significant from ANOVA p values a ralue hence regression model is not significant model henie it is not good.