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Kidney failure patients are commonly treated on dialysis machines that filter toxic substances from the blood. The appropriate "dose" for effective treatment depends, among other things, on duration of treatment and weight gain between treatments as a result of fluid buildup. To study the effects of these two factors on the number of days hospitalized (attributable to the disease) during a year, a random sample of '10 patients per group who had undergone treatment at a large dialysis facility was obtained. Treatment duration (factor \(A\) ) was categorized into two groups: short duration (average dialysis time for the year under four hours) and long duration (average dialysis time for the year equal to or greater than four hours). Average weight gain between treatments (factor \(B\) ) during the year was categorized into three groups: slight, moderate, and substantial. The data on number of days hospitalized follow. The transformed data \(Y^{\prime}=\log _{10}(Y+1)\) are to be used for the analysis. a. Obtain the fitted values and residuals for ANOVA model (19.23) for the transformed data. b. Prepare aligned residual dot plots for the treatments. What departures from ANOVA model (19.23) can be studied from these plots? What are your findings? c. Prepare a normal probability plot of the residuals. Also obtain the coefficient of correlation between the ordered residuals and their expected values under normality. Does the normality assumption appear to be reasonable here?