zerogreen

New Member
Hello,

We have been working on an assignment of t-test analysis, but the data we got look very puzzling and perplexing. I really need your help!

The task is to analyze a set of t-tests from a hypothetical study (1 paired t-test and 3 independent t-tests). But, the problem is... the set does not lead us to conclude anything!

Here is the plot: A research group conducted a study on effect of yoga therapy on anxiety. They had two groups, 1 experiment (taking a yoga course) and 1 control. The two groups took pre- and post tests to self-report their levels of anxiety.

As this is a practice of t-test, we got dataset of t-tests, instead of ANOVA, as follows;
1. Pre-test scores between the control & experiment groups;
2. Post-test scores between the two groups;
3. Pre – Post test scores between the two groups
4. Pre – Post test scores of all the participants (paired t-test).

Now, we’ve been struggling with this problem.
1. Pre-test scores between the two groups = No statistical difference
2. Post-test scores between the two groups = Yes, there is a difference.
3. Pre – Post test scores between the two groups = NO DIFFERENCE
4. Pre – Post test scores of all the participants (paired t-test) = There is a difference.

How can we interpret this? Why does the t-test No.3 NOT show difference? In our understanding, if the intervention (yoga) was effective, it should be seen in the results of Test No.2, No, 4, and also No. 3!?

For the independent tests, No 1 and 3 met the assumption of normality but No.2 did not. Thus, we used Welch’s t-test to analyze the data. The other two independent t-tests met the assumption.