Question

A consumer preference study involving three different bottle designs (A, B, and C) for the jumbo size of a new liquid laundry detergent was carried out using a randomized block experimental design, with supermarkets as blocks. Specifically, four supermarkets were supplied with all three bottle designs, which were priced the same. The following table gives the number of bottles of each design sold in a 24-hour period at each supermarket. If we use these data, SST, SSB, and SSE can be calculated to be 586.1667, 421.6667, and 1.8333, respectively. Results of a Bottle Design Experiment Supermarket, j Bottle Design, i 1 2 3 4 A 16 14 1 6 B 33 30 19 23 C 23 21 8 12 (a&b) Test the null hypothesis H0 that no differences exist between the effects of the bottle designs and supermarkets on mean daily sales. Set α = .05. Can we conclude that the different bottle designs have different effects on mean sales? (Round F to 2 decimal places and SS, MS to 3 decimal places. Leave no cells blank - be certain to enter "0" wherever required.) Analysis of Variance for factorl Tukey q.05 = 4.34, MSE = .306, s = .553, b = 4 Source DF SS MS F P Bottle 3 421.67 1.77e-07 Market 2 586.17 3.03e-08 Error 6 1.83 0.306 Total 11 1009.67 (c) Use Tukey simultaneous 95 percent confidence intervals to make pairwise comparisons of the bottle design effects on mean daily sales. Which bottle design(s) maximize mean sales? (Round your answers 2 decimal places. Negative amounts should be indicated by a minus sign.) AB: [ -18.20 , -15.80 ] AC: [ -7.95 , -5.55 ] BC: [ 9.05 , 11.45 ] Bottle design maximizes sales.

          A consumer preference study involving three different
bottle designs (A, B, and C) for the jumbo size of a new liquid
laundry detergent was carried out using a randomized block
experimental design, with supermarkets as blocks. Specifically,
four supermarkets were supplied with all three bottle designs,
which were priced the same. The following table gives the number of
bottles of each design sold in a 24-hour period at each
supermarket. If we use these data, SST, SSB, and SSE can be
calculated to be 586.1667, 421.6667, and 1.8333, respectively.
Results of a Bottle Design Experiment Supermarket, j Bottle Design,
i 1 2 3 4 A 16 14 1 6 B 33 30 19 23 C 23 21 8 12 (a&b) Test the
null hypothesis H0 that no differences exist between the effects of
the bottle designs and supermarkets on mean daily sales. Set α =
.05. Can we conclude that the different bottle designs have
different effects on mean sales? (Round F to 2 decimal places and
SS, MS to 3 decimal places. Leave no cells blank - be certain to
enter "0" wherever required.) Analysis of Variance for factorl
Tukey q.05 = 4.34, MSE = .306, s = .553, b = 4 Source DF SS MS F P
Bottle 3 421.67 1.77e-07 Market 2 586.17 3.03e-08 Error 6 1.83
0.306 Total 11 1009.67 (c) Use Tukey simultaneous 95 percent
confidence intervals to make pairwise comparisons of the bottle
design effects on mean daily sales. Which bottle design(s) maximize
mean sales? (Round your answers 2 decimal places. Negative amounts
should be indicated by a minus sign.) AB: [ -18.20 , -15.80 ] AC: [
-7.95 , -5.55 ] BC: [ 9.05 , 11.45 ] Bottle design maximizes
sales.

Added by Virginia M.

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