Bonferroni's Method for Pairwise Multiple Comparisons

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The Bonferroni method is a post-hoc procedure conducted after an ANOVA test or Kruskal-Wallis test whenever the null hypothesis has been rejected and have concluded a significant difference in at least 2 means. It is a pairwise comparison that distinguishes which groups are significantly different.
Bonferroni uses confidence intervals to conclude a significant difference. The interval is calculated using the formula below:
Where B=Z_((1−α/2g) ) and g is the number of pairwise comparisons of interest (usually all pairwise comparisons are investigated). g is calculated by g=k(k−1)/2.
Q. Using the same example we used in our previous lesson,
Based on the Kruskal-Wallis test, we concluded that at least two treatment group means differed @ 0.05 significance level.
Use the Bonferroni method to calculate confidence intervals for all the pairwise differences between the treatments. Use the 95% confidence level to find out which ones are significantly different.

[@dgnbfujbvgjnv5552]

What if you want to test only if T4 is different from 1 2 and 3? Would the test statistic be different from that of comparing all pairs?

[@madhurasutar5332]

Very well explained👍👍

[@arisdikrannisan3578]

well explained!

[@annieleonhart2975]

Why is the mean so high? why is the mean of (0, 0, 1, 1, 2) equal (Rbar_1 = 8.1) ?

[@tanakadzingai3412]

find benforreni t value given Alpha is 0.05 P=m=2 n=8
Please help ASAP

[@Jawad_Ali876]

How you calculate R bar

[@smartraya1047]

Great

[@eileenmitchell2856]

If using a tscore (instead of z) - what is your degrees of freedom?

[@andrewhoughton1024]

t(DFE or n - 2) distribution