Consider the following data from a repeated-measures design. You want to use a repeated-measures t test to test the null hypothesis H0: µD = 0 (the null hypothesis states that the mean difference for the general population is zero). The data consist of five observations, each with two measurements, A and B, taken before and after a treatment. Assume the population of the differences in these measurements are normally distributed. Observation A B 1 1 3 2 3 4 3 5 7 4 4 4 5 8 9 You conduct a two-tailed test at α = .05. To find the critical value (in the table) you first need to get the degrees of freedom, which is [ Select ] ["3", "4", "5"] The critical values (the values for t-scores that separate the tails from the main body of the distribution, forming the critical region) are ± [ Select ] ["2.571", "2.776", "3.182", "4.032"] Based on this our finding [ Select ] ["is", "is not"] significant and we [ Select ] ["reject", "fail to reject"] the null hypothesis.
Consider the following data from a repeated-measures design. You want to use a repeated-measures t test to test the null hypothesis H0: µD = 0 (the null hypothesis states that the
| Observation | A | B |
| 1 | 1 | 3 |
| 2 | 3 | 4 |
| 3 | 5 | 7 |
| 4 | 4 | 4 |
| 5 | 8 | 9 |
You conduct a two-tailed test at α = .05. To find the critical value (in the table) you first need to get the degrees of freedom, which is [ Select ] ["3", "4", "5"]
The critical values (the values for t-scores that separate the tails from the main body of the distribution, forming the critical region) are ± [ Select ] ["2.571", "2.776", "3.182", "4.032"]
Based on this our finding [ Select ] ["is", "is not"] significant and we [ Select ] ["reject", "fail to reject"] the null hypothesis.
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