Solution concentration . A chemist studied the concentration of a solution ( * ) over time ( * ) . Fifteen identical solutions were prepared . The...
I only need o finish Q3.16. I include Q3.15 just for reference. Please use R if needed. Please include any graphs you made in your answer.
3. 15. Solution concentration . A chemist studied the concentration of a solution ( * ) over time ( * ) .Fifteen identical solutions were prepared . The 15 solutions were randomly divided into fivesets of three , and the five sets were measured , respectively , after 1 , 3 , 5 , 7 , and 9 hours . Theresults follow .3137415Xi .9Yi :. Of60. 08...2.842.573. 10a. Fit a linear regression function .b. Perform the { test to determine whether or not there is lack of fit of a linear regressionfunction; use a _ . 025 . State the alternatives , decision rule , and conclusion .C . Does the test in part ( b ) indicate what regression function is appropriate when it leads to theconclusion that lack of fit of a linear regression function exists ? Explain .3.16 / Refer to Solution concentration Problem 3. 15 .2 . Prepare a scatter plot of the data . What transformation of !' might you try , using the prototypepatterns in Figure 3. 15 to achieve constant variance and linearity ?b. Use the Box- Cox procedure and standardization ( 3.36 ) to find an appropriate powertransformation . Evaluate SSE for X _ _. 2. _. 1 , 0. . 1, . 2. What It transformation of Y issuggested ?c . Use the transformation * ' = log 10 *' and obtain the estimated linear regression function forthe transformed data .d . Plot the estimated regression line and the transformed data . Does the regression line appearto be a good fit to the transformed data ?c . Obtain , the residuals and plot them against the fitted values . Also prepare a normal probabilityplot . What do your plots show ?F. Express the estimated regression function in the original units .
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