The operations manager for a soft drink distributor is interested in obtaining a more uniform/consistent fill height in the bottles filled during the bottling process at the distributions center. Supposedly, available machinery fills each bottle to the correct level, but in practice, there is variation around the specified target. Typically, 25 psi is desirable for the equipment on hand. Two additional variables may affect the variation associated with the filling process: percent carbonation (10% or 12%) and or line speed (either 210, 240, 270, or 300 bottles per minute). Use Two ANOVA to determine if percent carbonation (Factor 1 and Line Speed Factor 2) have effect on variation in bottle fill. The response variable is bottle fill in milliliter Factor 1 is percent carbonation Factor 2 is Line Speed Problem Definition: Conduct Two Way ANOVA with interaction to test mean deviation in bottle fill. In this case higher mean deviation does not produce the desired result. Deviation is the miss from the desired fill height. Complete the following for the two-way ANOVA. The finished report should contain the following in the order specified. Complete a six-step process to determine if the variances of the eight cell combinations of Line Speed and Carbonation on Bottle fill height are equal. You may use p-values to test hypothesis of equal variances. Remember, there is one variance per cell (combination of per treatment of Percent Carbonation and Line Speed on Bottle Fill). *Hint: Eight cells require eight variances. Use NP Plot to satisfy the assumption of normality. Recall residuals are plotted on the NP Plot e= -bar (the cell mean). Each dot on the plot is a residual. Prepare six step process for Interaction, Row Factor and Column Factor. Each requires six step process. Remember to test the null of no interaction first. If FTR you must test the remaining hypotheses. Use Minitab to analyze the data and test the hypotheses. Use both p values and critical value/critical ratio to all hypothesis tests. Complete Tukey tests on any significant outcomes (use six step process). Address results of Tukey test in regard to determining the best combination of row and column factor to produce most accurate bottle fill.