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Thank a lot, but I have a bit special case, in about 90% of my cases after the rejection of the null hypothesis one sees thanks to pairwise comparisons (post-hoc with Bonferroni corecture) which groups differ significantly. However, I have a few cases where KH rejects the null hypothesis (somewhat close but already 0.044) but pairwise comparisons show no significant differences. I thought I might look at the post-hoc values without Bonferorroni correctors and base the significance of the differences on them, because some of the significant values are already below 0.05. Is it possible to understand such an approach? Are the corrected significances according to Bonferroni possibly too imprecise if KH is just below 0.05?
Thanks a lot Dr! I would be thankful if you also made a video on how exactly we can find out whether our data are normally distributed because this will tell us whether we need ro run a parametric or non-parametric test.
You can perform a Shapiro-Wilks Test for checking the normality of the data. The null hypothesis for this test is that the data is normally distributed. So you want the p value to be more than 0.05 at 95% confidence interval to accept the null hypothesis. Go to analyze => Descriptive Stattistics => Explore => in the dependent list put your variable (age, height, income, or whatever it is) => options => click and check on 'Histogram' and 'normality plot with tests' => continue => ok, and you are done. Note down the value for Shapiro-Wilks and you are ready to assess whether your data is normally distributed or not.
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Thank you sir for your precious explanation on the test. Really appreciate!
Thank you Doc, anyone know how to compute compact letter display?
Thank a lot, but I have a bit special case, in about 90% of my cases after the rejection of the null hypothesis one sees thanks to pairwise comparisons (post-hoc with Bonferroni corecture) which groups differ significantly. However, I have a few cases where KH rejects the null hypothesis (somewhat close but already 0.044) but pairwise comparisons show no significant differences. I thought I might look at the post-hoc values without Bonferorroni correctors and base the significance of the differences on them, because some of the significant values are already below 0.05. Is it possible to understand such an approach? Are the corrected significances according to Bonferroni possibly too imprecise if KH is just below 0.05?
Thanks a lot Dr! I would be thankful if you also made a video on how exactly we can find out whether our data are normally distributed because this will tell us whether we need ro run a parametric or non-parametric test.
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You can perform a Shapiro-Wilks Test for checking the normality of the data. The null hypothesis for this test is that the data is normally distributed. So you want the p value to be more than 0.05 at 95% confidence interval to accept the null hypothesis.
Go to analyze => Descriptive Stattistics => Explore => in the dependent list put your variable (age, height, income, or whatever it is) => options => click and check on 'Histogram' and 'normality plot with tests' => continue => ok, and you are done.
Note down the value for Shapiro-Wilks and you are ready to assess whether your data is normally distributed or not.
Can the Bonferroni test be used after the Karuskal-Wallis test? Does the Bonferroni test require that the data depend on a normal distribution or not?
I assume the Dunn test was used for the post hoc test?
How do you report this? What can be stated as the name of the post hoc test used?
Thank you so much sir for valuable video
Welldone, sir..! Thank you so much!!
Thanks a lot, doctor. Very much usual video.
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Can the Kruskal Wallis test statistic (H) be negative? What does it mean? You have H=-9.500 p=0,012 (Control- 1 week)
thank you sir for the video. however, I have one question. the significant level after post hoc test is still 0.05?
I am having a difficulty on what letter/symbol I should use in my APA Format report in Post Hoc. Should I use H or F?
And oh, how do I do it?
Can the grouping variable be ordinal? Or only nominal accepted
It is for both
Ordinal and nominal variables
😀 !