The following data represent the results from an independent-measures study comparing two treatment conditions. Both tables contain the same data, but are formatted differently. Treatment One One One One One One Two Two Two Two Two Two 6.5 8.2 7.1 6 5.6 4.6 Treatment Treatment One Two Response 6.5 8.2 7.1 6 5.6 4.6 3.3 2 2.5 2.1 F* test statistic: p-value: 4.5 4.6 t* test statistic: p-value: 3.3 2 2.5 Conduct ANOVA with a = 0.05 for this data and calculate the F. test statistic and p-value. Round your answer to three decimal places. Assume all population and ANOVA requirements are met. 2.1 4.5 4.6 Now, conduct a t-test with a = 0.05 on the same data and calculate the t* test statistic and p-value. Round your answer to three decimal places. Observing the p-values, was there a difference in the result of the hypothesis test? O Yes, the p-values are different enough to change the outcome of the test. No, the p-values aren't that far off where it would change the outcome of the test.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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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. Both tables contain the same data, but are formatted differently.
Treatment
One
One
One
One
One
One
Two
Two
Two
Two
Two
Two
Treatment Treatment
One
Two
6.5
8.2
7.1
6
5.6
4.6
Response
6.5
8.2
7.1
6
5.6
4.6
3.3
2
2.5
2.1
4.5
4.6
F* test statistic:
p-value:
Conduct ANOVA with a = 0.05 for this data and calculate the F. test statistic and p-value. Round your
answer to three decimal places. Assume all population and ANOVA requirements are met.
3.3
2
2.5
2.1
4.5
4.6
t* test statistic:
p-value:
Now, conduct a t-test with a = 0.05 on the same data and calculate the t* test statistic and p-value.
Round your answer to three decimal places.
Observing the p-values, was there a difference in the result of the hypothesis test?
O Yes, the p-values are different enough to change the outcome of the test.
No, the p-values aren't that far off where it would change the outcome of the test.
Transcribed Image Text:The following data represent the results from an independent-measures study comparing two treatment conditions. Both tables contain the same data, but are formatted differently. Treatment One One One One One One Two Two Two Two Two Two Treatment Treatment One Two 6.5 8.2 7.1 6 5.6 4.6 Response 6.5 8.2 7.1 6 5.6 4.6 3.3 2 2.5 2.1 4.5 4.6 F* test statistic: p-value: Conduct ANOVA with a = 0.05 for this data and calculate the F. test statistic and p-value. Round your answer to three decimal places. Assume all population and ANOVA requirements are met. 3.3 2 2.5 2.1 4.5 4.6 t* test statistic: p-value: Now, conduct a t-test with a = 0.05 on the same data and calculate the t* test statistic and p-value. Round your answer to three decimal places. Observing the p-values, was there a difference in the result of the hypothesis test? O Yes, the p-values are different enough to change the outcome of the test. No, the p-values aren't that far off where it would change the outcome of the test.
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