According to Aron, Aron,
& Coups (2009), comparison distribution represents the population situation
if the null hypothesis is true. It is the distribution that you compare the
score of your samples to. This distribution is the difference between means. In
a t test for independent means, the
distribution of differences is 0. Comparison distribution is important in
hypothesis testing because the significance can help you reject or fail to
reject the null hypothesis.
Aron, A., Aron, E. N., & Coups, E. J. (2009). Statistics
for psychology (5th ed). Upper Saddle River, NJ: Pearson/Prentice Hall.
Plagiarism:
Using someone else's work without giving proper credit, is plagiarism. If you use my work, please reference it.
interesting that you mentino t-tests, as i am using it for z-testing.
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