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The sole exception to this rule is that no difference between two means can be declared significant if the two means concerned are both contained in a subset of the means which has a non-significant range. An algorithm for performing the test is as follows: 1.Rank the sample means, largest to smallest. 2.
Describe the differences in proportions using the rule of thumb criteria set out by Cohen. [1] Namely, h = 0.2 is a "small" difference, h = 0.5 is a "medium" difference, and h = 0.8 is a "large" difference. [2] [3] Only discuss differences that have h greater than some threshold value, such as 0.2. [4]
It was named after Student (1927), [2] D. Newman, [3] and M. Keuls. [4] This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA). [1] The Newman–Keuls method is similar to Tukey's range test as both procedures use studentized range ...
The actual difference is not usually a good way to compare the numbers, in particular because it depends on the unit of measurement. For instance, 1 m is the same as 100 cm, but the absolute difference between 2 and 1 m is 1 while the absolute difference between 200 and 100 cm is 100, giving the impression of a larger difference. [4]
This is the smallest value for which we care about observing a difference. Now, for (1) to reject H 0 with a probability of at least 1 − β when H a is true (i.e. a power of 1 − β), and (2) reject H 0 with probability α when H 0 is true, the following is necessary: If z α is the upper α percentage point of the standard normal ...
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