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It can be used to correctly interpret the statistical significance of the difference between means that have been selected for comparison because of their extreme values. The method was initially developed and introduced by John Tukey for use in Analysis of Variance (ANOVA), and usually has only been taught in connection with ANOVA.
To determine if there is a significant difference between two means with equal sample sizes, the Newman–Keuls method uses a formula that is identical to the one used in Tukey's range test, which calculates the q value by taking the difference between two sample means and dividing it by the standard error:
The new multiple range test proposed by Duncan makes use of special protection levels based upon degrees of freedom.Let , = be the protection level for testing the significance of a difference between two means; that is, the probability that a significant difference between two means will not be found if the population means are equal.
Researchers focusing solely on whether their results are statistically significant might report findings that are not substantive [46] and not replicable. [47] [48] There is also a difference between statistical significance and practical significance. A study that is found to be statistically significant may not necessarily be practically ...
The mean word.recall in the 0 drug.dose group is 2. The mean word.recall in the 1 drug.dose group is 6. The difference between treatment groups in the mean word.recall is 6 – 2 = 4. The difference in word.recall between drug doses is significant (p=0.00805). Perform a linear regression of the same data.
A significant omnibus F test in ANOVA procedure, is an in advance requirement before conducting the Post Hoc comparison, otherwise those comparisons are not required. If the omnibus test fails to find significant differences between all means, it means that no difference has been found between any combinations of the tested means.
The Student's t distribution plays a role in a number of widely used statistical analyses, including Student's t test for assessing the statistical significance of the difference between two sample means, the construction of confidence intervals for the difference between two population means, and in linear regression analysis.
When measuring differences between proportions, Cohen's h can be used in conjunction with hypothesis testing. A "statistically significant" difference between two proportions is understood to mean that, given the data, it is likely that there is a difference in the population proportions. However, this difference might be too small to be ...