A marketing organization wishes to study the effects of four sales methods on weekly sales of a product. The organization employs a randomized block design in which three salesman use each sales method. The results obtained are given in the following table, along with the output of a randomized block ANOVA of these data.
Salesman, j | |||
Sales Method, i | A | B | C |
1 | 32 | 29 | 30 |
2 | 32 | 30 | 28 |
3 | 28 | 25 | 23 |
4 | 24 | 24 | 23 |
Analysis of Variance | ||||
Source | DF | Sum of Squares | Mean Square | F Ratio |
Model | 5 | 119.33333 | 23.8667 | 19.5273 |
Error | 6 | 7.33333 | 1.2222 | Prob > F |
C. Total | 11 | 126.66667 | 25.0889 | 0.0012* |
Effect Tests | |||||
Source | Nparm | DF | Sum of Squares | F Ratio | Prob > F |
Method | 3 | 3 | 100.666670 | 27.4545 | 0.0007* |
Salesman | 2 | 2 | 18.666670 | 7.6364 | 0.0224* |
Least Squares Means Estimates | |||
Method | Estimate | Salesman | Estimate |
1 | 30.333333 | A | 29.000000 |
2 | 30.000000 | B | 27.000000 |
3 | 25.333333 | C | 26.000000 |
4 | 23.666667 |
Tukey HSD All Pairwise Comparisons
Quantile = 3.46171, Adjusted DF = 60, Adjustment = Tukey
Method -Method | Difference | Std Error | t Ratio | Prob>|t| | Lower 95% | Upper 95% | |
1 | 2 | 0.333333 | 0.9026709 | 0.37 | 0.9812 | −2.79145 | 3.458110 |
1 | 3 | 5.000000 | 0.9026709 | 5.54 | 0.0059* | 1.87522 | 8.124780 |
1 | 4 | 6.666667 | 0.9026709 | 7.39 | 0.0013* | 3.54189 | 9.791450 |
2 | 3 | 4.666667 | 0.9026709 | 5.17 | 0.0083* | 1.54189 | 7.791450 |
2 | 4 | 6.333333 | 0.9026709 | 7.02 | 0.0017* | 3.20855 | 9.458110 |
3 | 4 | 1.666667 | 0.9026709 | 1.85 | 0.3397 | −1.45811 | 4.791450 |
Use Tukey simultaneous 95 percent confidence intervals to make pairwise comparisons of the sales method effects on mean weekly sales. Which sales method(s) maximize mean weekly sales? (Round your answers to 3 decimal places. Negative amounts should be indicated by a minus sign.)
Method 1-Method 2:
Method 1-Method 3:
Method 1-Method 4:
Method 2-Method 3:
Method 2-Method 4:
Method 3-Method 4:
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