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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
27 The Excel output of a one-way ANOVA of the Bottle Design Study Data is shown below.
Design A 5
Design B 5 163
Design C 5 121
Source of Variation SS df MS Between Groups 656.4000 2 328.2000 Within Groups
Total 61.2 12.0
14 5.1000 F P-Value F crit
06 (a) Test the null hypothesis that ?A, ?B, and ?C are equal by setting ? = .05. Based on this test, can
we conclude that bottle designs A, B, and C have different effects on mean daily sales? (Round
your answers to 2 decimal places. Leave no cells blank - be certain to enter "0" wherever
pvalue H0: bottle design
(Click to select) have an impact on sales.
(Click to select) (b) Consider the pairwise differences ?B ? ?A, ?C ? ?A , and ?C ? ?B. Find a point estimate of and a
Tukey simultaneous 95 percent confidence interval for each pairwise difference. Interpret the results
in practical terms. Which bottle design maximizes mean daily sales? (Round your answers to 2
decimal places. Negative amounts should be indicated by a minus sign.)
Point estimate Confidence interval
, ?C ??A: ,[ , ?C ??B: ,[ , Bottle design maximizes sales.
(Click to select) (c) Find a 95 percent confidence interval for each of the treatment means ?A, ?B, and ?C. Interpret
these intervals. (Round your answers to 2 decimal places. Negative amounts should be
indicated by a minus sign.)
, ?B: [ , ? C: [ ,
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