A consumer preference study compares the effects of three different bottle designs (A, B, and C) on sales of a popular fabric softener. A completely randomized design is employed. Specifically, 15 supermarkets of equal sales potential are selected, and 5 of these supermarkets are randomly assigned to each bottle design. The number of bottles sold in 24 hours at each supermarket is recorded. The data obtained are displayed in the following table.

Bottle Design Study Data A B C 18 34 25 17 32 28 18 30 22 17 33 28 16 34 25 The Excel output of a one-way ANOVA of the Bottle Design Study Data is shown below. SUMMARY Groups Count Sum Average Variance Design A 5 86 17.2 . 7 Design B 163 32 . 6 2. 8 Design C 5 128 25 . 6 6.3 ANOVA Source of Variation SS df MS F P-Value F crit Between Groups 594.5333 2 297 . 2667 91. 00 5. 60E-08 3. 88529 Within Groups 39 .2 12 .0 3. 2670 Total 633. 7333 14{a} Test the null hypothesis that Inn, 345, and ,uc are equal by setting a = .05. Based on this test, can we conclude that bottle designs A, B, and C have different effects on mean clailgir sales? (Round your answers to 2 decimal places.) H0: bottle design _ have an impact on sales. {In} Consider the pairwise dierences #5 M.- #c pa , and ya \"3- Find a point estimate of and a TukegiI simultaneous 95 percent condence interval for each paimise difference. Interpret the results in practical terms. Which bottle design maximizes mean dailyr sales? (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.) Point estimate Condence interval uB uA: uC uA: uC uB: "- {cl Find a 95 percent condence interval for each of the treatment means My \"3- and go Interpret these intervals. [Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.} Condence interval M! l HE: [ HO: [