A repeated-measures experiment comparing only two treatments can be evaluated with either a t statistic or an ANOVA. As we found with the independent-measures design, the t test and the ANOVA produce equivalent conclusions, and the two test statistics are related by the equation F = t2.
The following data are from a repeated-measures study.
|
Subject
|
Treatment 1
|
Treatment 2
|
Difference
|
|
1
|
2
|
3
|
+1
|
|
2
|
2
|
3
|
+1
|
|
3
|
1
|
5
|
+4
|
|
4
|
2
|
3
|
+1
|
(a) Use a repeated-measures t statistic with α = 0.05 to determine whether the data provide evidence of a significant difference between the two treatments. (Caution: ANOVA calculations are done with the X values, but for t you use the difference scores. Round your answers to three decimal places.)
Conclusion Reject the null hypothesis. There are significant differences between the two treatments. Fail to reject the null hypothesis. There are not significant differences between the two treatments. Fail to reject the null hypothesis. There are significant differences between the two treatments. Reject the null hypothesis. There are not significant differences between the two treatments.