The Test Statistic
Tukey's test is based on a formula very similar to that of the t-test. In fact, Tukey's test is essentially a t-test, except that it corrects for experiment-wise error rate (when there are multiple comparisons being made, the probability of making a type I error increases — Tukey's test corrects for that, and is thus more suitable for multiple comparisons than doing a number of t-tests would be).
The formula for Tukey's test is:
where YA is the larger of the two means being compared, YB is the smaller of the two means being compared, and SE is the standard error of the data in question.
This qs value can then be compared to a q value from the studentized range distribution. If the qs value is larger than the qcritical value obtained from the distribution, the two means are said to be significantly different.
Since the null hypothesis for Tukey's test states that all means being compared are from the same population (i.e. μ1 = μ2 = μ3 = ... = μn), the means should be normally distributed (according to the central limit theorem). This gives rise to the normality assumption of Tukey's test.
Read more about this topic: Tukey's Range Test
Famous quotes containing the word test:
“He who has never failed somewhere, that man can not be great. Failure is the true test of greatness. And if it be said, that continual success is a proof that a man wisely knows his powers,—it is only to be added, that, in that case, he knows them to be small.”
—Herman Melville (1819–1891)