The following data represent the results from an independent-measures experiment comparing three treatment conditions. Use SPSS to conduct an analysis of variance with α=0.05α=0.05 to determine whether these data are sufficient to conclude that there are significant differences between the treatments.
Treatment A | Treatment B | Treatment C |
---|---|---|
2 | 4 | 5 |
4 | 2 | 7 |
4 | 4 | 8 |
2 | 7 | 9 |
3 | 3 | 11 |
F-ratio =
p-value =
Conclusion:
The results obtained above were primarily due to the mean for the
third treatment being noticeably different from the other two
sample means. For the following data, the scores are the same as
above except that the difference between treatments was reduced by
moving the third treatment closer to the other two samples. In
particular, 3 points have been subtracted from each score in the
third sample.
Before you begin the calculation, predict how the changes in the
data should influence the outcome of the analysis. That is, how
will the F-ratio for these data compare with the
F-ratio from above?
Treatment A | Treatment B | Treatment C |
---|---|---|
2 | 4 | 2 |
4 | 2 | 4 |
4 | 4 | 5 |
2 | 7 | 6 |
3 | 3 | 8 |
F-ratio =
p-value =
Conclusion:
a)
By using One-way ANOVA calculator:
Source | SS | DF | MS | F |
Between-treatments | 70 | 2 | 35 | 11.05263 |
Within-treatments | 38 | 12 | 3.1667 | |
Total | 108 | 14 |
F-ratio = 11.05263
P-value = 0.001897
The result is significant at p < 0.05.
There is a significant difference between treatments.
b)
By using One-way ANOVA calculator:
Source | SS | DF | MS | F |
Between-treatments | 10 | 2 | 5 | 1.57895 |
Within-treatments | 38 | 12 | 3.1667 | |
Total | 48 | 14 |
F-ratio = 1.57895
P-value = 0.246181
The result is not significant at p < 0.05.
These data do not provide evidence of a difference between the treatments.
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