One of the advantages of a repeated-measures design is that it removes the individual differences from the error variance and increases the likelihood of rejecting the null hypothesis. The following data were obtained from a research study comparing three treatment conditions. Treatment 1 Treatment 2 Treatment 3 6 8 10 G=48 5 5 5 1 2 3 0 1 2 T=12 SS=26 T=16 SS=30 T=20 SS=38 a. Assume that the data are from an independent-measures study (like in Chapter 12 normal ANOVA) using three separate samples, each with n=4 participants, and use an independent-measures ANOVA with a=.05 to test for significant differences among the three treatments. b.Assume that the data are from a repeated-measures study using one sample of n=4 participants and use a repeated-measures ANOVA with a=.05 to test for significant differences among the three treatments. c. Compare your results from part A and part B.
One of the advantages of a repeated-measures design is that it removes the individual differences from the error variance and increases the likelihood of rejecting the null hypothesis. The following data were obtained from a research study comparing three treatment conditions. Treatment 1 Treatment 2 Treatment 3 6 8 10 G=48 5 5 5 1 2 3 0 1 2 T=12 SS=26 T=16 SS=30 T=20 SS=38 a. Assume that the data are from an independent-measures study (like in Chapter 12 normal ANOVA) using three separate samples, each with n=4 participants, and use an independent-measures ANOVA with a=.05 to test for significant differences among the three treatments. b.Assume that the data are from a repeated-measures study using one sample of n=4 participants and use a repeated-measures ANOVA with a=.05 to test for significant differences among the three treatments. c. Compare your results from part A and part B.
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- One of the advantages of a repeated-measures design is that it removes the individual differences from the error variance and increases the likelihood of rejecting the null hypothesis. The following data were obtained from a research study comparing three treatment conditions.
Treatment 1 |
Treatment 2 |
Treatment 3 |
|
6 |
8 |
10 |
G=48 |
5 |
5 |
5 |
|
1 |
2 |
3 |
|
0 |
1 |
2 |
|
T=12 SS=26 |
T=16 SS=30 |
T=20 SS=38 |
|
a. Assume that the data are from an independent-measures study (like in Chapter 12 normal ANOVA) using three separate samples, each with n=4 participants, and use an independent-measures ANOVA with a=.05 to test for significant differences among the three treatments.
b.Assume that the data are from a repeated-measures study using one sample of n=4 participants and use a repeated-measures ANOVA with a=.05 to test for significant differences among the three treatments.
c. Compare your results from part A and part B.
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