Kruskal-Wallis-Test in SPSS - calculation and interpretation
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- čas přidán 15. 06. 2024
- I'll show how to conduct the Kruskal-Wallis-test and interpret the results using SPSS statistics.
➡️ Watch next: • Post hoc tests for the...
General information:
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The Kruskal-Wallis-test is a non-parametric statistical method that is used in place of the one-way ANOVA when the data is not normally distributed. This test is used to assess whether the medians of at least three groups are different. You can use a dependent variable that is at least on the ordinal scale.
For example:
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I have three groups. A control group and two intervention groups. The first intervention consisted of meditation and the second intervention group had mentors.
I want to test the grade point average (GPA) for differences across the three groups using the Kruskal-Wallis-test.
Calculating the required sample size:
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🎥 • Kruskal-Wallis-Test - ...
⏰ Timestamps:
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0:00 Introduction
0:18 Example
0:36 Requirements for the Kruskal-Wallis-test
0:43 Descriptive statistics as a first look
1:11 Kruskal-Wallis-test calculation
2:03 Interpreting the results of the Kruskal-Wallis-test
If you have any questions or suggestions regarding Kruskal-Wallis-test in SPSS - calculation and interpretation, please use the comment function. Thumbs up or down to decide if you found the video helpful. #statisticampc
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➡ Follow-up for a Kruskal-Wallis-test: czcams.com/video/AvXAU8IVqRM/video.html
Your videos are so helpful! I will watch all of your videos. I want to learn all of it.
Glad to hear that. Keep it up!
Best Regards, Björn.
@@statorialskeep it up, I will wait for your next upload. ❤️
Great video! But how do I interpret the pairwise comparison charts (the triangle shaped ones)? I've been searching and I'm yet to find out what do they mean.
Thanks for he positive feedback. The triangle is just a different way of presenting the information of the pairwise comparisons for the Kruskal-Wallis test. Depending on how you defined your Alpha in the K-W-Test, the lines represent, if the comparisons of the groups from start of the line compared to the end of the line is "significant", aka. the p-value low enough that the effect can be be observed due to chance. So, a blue line means that the groups that are connected through the line, are different in regard to mean ranks. A red line means they are not. If you have more groups the form will have more lines - one for each pairwise comparison.
Cheers, Björn.