Marketing Managers | Marketing Research | Advertising | |
5 | 8 | 6 | |
4 | 8 | 7 | |
3 | 7 | 6 | |
4 | 7 | 5 | |
5 | 8 | 6 | |
3 | 7 | 6 | |
Total(yi) | 24 | 45 | 36 |
Averages y̅i | 4 | 7.5 | 6 |
Treatment Effect | 4 - 5.83 = -1.83 | 7.5 - 5.83 = 1.67 | 6 - 5.83 = 0.17 |
Sum of Squares | Degree of freedom | Mean Square | F0 = MST / MSE | P value | |
Treatment | 36.99 | 2 | 18.5 | 37 | < 0.01 |
Error | 7.5 | 15 | 0.5 | ||
Total | 44.49 | 17 |
Part a)
SST = 36.99
SSE = 7.5
MST = 18.5
MSE = 0.5
Part b)
Test Statistic :-
f = MS treatment / MS error = 37
Reject null hypothesis if P value < α = 0.05
Since P value = 0 < 0.05, hence we reject the null
hypothesis
Conclusion :- Treatment means differs
part c)
t(α/2 , N-a ) = 2.13 ( Critical value from t table )
LSD =
= 0.87 Since the design is balanced n1 = n1 = n3 = n
= | 4 - 7.5 | = 3.5
= | 4 - 6 | = 2
= | 7.5 - 6 | = 1.5
Since | 4 - 7.5 | > 0.87, we conclude that the population means
µ1. and µ2. differ.
Since | 4 - 6 | > 0.87, we conclude that the population means
µ1. and µ3. differ.
Since | 7.5 - 6 | > 0.87, we conclude that the population means
µ2. and µ3. differ.
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