The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Response One 6.8 One 5.4 One 8.5 One 6.8 One 7.5 One One One Two Two Two Two Two Two Two Two Treatment One 6.8 5.4 8.5 6.8 7.5 5.3 7.1 7.3 5.3 7.1 7.3 3.6 2.3 3 4.2 1.9 1.3 3.2 4.9 Treatment Two F-ratio: 44.841 X p-value: 0.000 3.6 2.3 3 4.2 1.9 1.3 3.2 4.9 Conduct ANOVA with a = 0.05 for this data and calculate the F-ratio and p-value. Round your answer to three decimal places. Assume all population and ANOVA requirements are met. Now, conduct a t-test with a = 0.05 on the same data and calculate the t-statisitc and p-value. Round your answer to three decimal places. t-statistic: 6.6961 X p-value: 0.000 08 Observing the p-values, was there a difference in the result of the hypothesis test? No, the p-values aren't that far off where it would change the outcome of the test. Yes, the p-values are different enough to change the outcome of the test.

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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The following data represent the results from an independent-measures study comparing two treatment
conditions.
Treatment Response
One
6.8
One
5.4
One
8.5
One
6.8
One
7.5
One
One
One
Two
Two
Two
Two
Two
Two
Two
Two
Treatment
One
6.8
5.4
8.5
6.8
7.5
5.3
7.1
7.3
Treatment
Two
F-ratio: 44.841 X
p-value: 0.000
5.3
7.1
7.3
3.6
2.3
3
4.2
1.9
1.3
3.2
4.9
Conduct ANOVA with a = 0.05 for this data and calculate the F-ratio and p-value. Round your answer to
three decimal places. Assume all population and ANOVA requirements are met.
08
3.6
2.3
3
4.2
1.9
1.3
3.2
4.9
Now, conduct a t-test with a = 0.05 on the same data and calculate the t-statisitc and p-value. Round
your answer to three decimal places.
t-statistic: 6.6961 X
p-value: 0.000
08
Observing the p-values, was there a difference in the result of the hypothesis test?
No, the p-values aren't that far off where it would change the outcome of the test.
Yes, the p-values are different enough to change the outcome of the test.
Transcribed Image Text:The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Response One 6.8 One 5.4 One 8.5 One 6.8 One 7.5 One One One Two Two Two Two Two Two Two Two Treatment One 6.8 5.4 8.5 6.8 7.5 5.3 7.1 7.3 Treatment Two F-ratio: 44.841 X p-value: 0.000 5.3 7.1 7.3 3.6 2.3 3 4.2 1.9 1.3 3.2 4.9 Conduct ANOVA with a = 0.05 for this data and calculate the F-ratio and p-value. Round your answer to three decimal places. Assume all population and ANOVA requirements are met. 08 3.6 2.3 3 4.2 1.9 1.3 3.2 4.9 Now, conduct a t-test with a = 0.05 on the same data and calculate the t-statisitc and p-value. Round your answer to three decimal places. t-statistic: 6.6961 X p-value: 0.000 08 Observing the p-values, was there a difference in the result of the hypothesis test? No, the p-values aren't that far off where it would change the outcome of the test. Yes, the p-values are different enough to change the outcome of the test.
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