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Testing the Assumptions for Spearman's Rank-Order Correlation in SPSS
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- Опубліковано 3 тра 2016
- This video demonstrates how to test the assumptions for Spearman’s rank-order correlation (Spearman’s rho) in SPSS. The assumptions for Spearman’s rho include an ordinal or higher level of measurement and a monotonic relationship.
thank you Dr. I watched most of your tutorials and they are very useful. my question to you is can I use spearman instead of Pearson if all Pearson assumptions are violated? normality.. outliers and linearity?
oh thank you thank you thank you!!!!!! I appreciate this video!!!!!
it was very useful, thank you professor
Very useful video, many thanks.
I have a question; I have 10 variables one is based on likert scale (1,2,3,4 or 5) and the other variables are based on 1 or 0 (yes or no). Which method could be used to test the correlation between the 1st variable and the others. thx.
My methodolgist does not want me to use the term weak or strong...but Cohens (1992) definitions of small, medium, and large to describe the correlation. Do you have the reference article that states how the spearman should be interrupted?
What would be a proper test for scale (e.g: usage frequency) and ordinal (education level)?
Soooo if all of my variables there's no relationship shown in scatter plot. is that bad? where do i go from there? i mean initially i thought there'd be some type of relationship but there's none. what does that mean for my research? how do i even explain that?
If there are just 3 straight lines because there are 3 categories in the DV, does that mean that it is still monotonic?
One of my variables has ordinal data but the other has nominal data. Which statistical test should I use in this case?
Does this work if you have multiple dependent variables? Also can I find the average of the 3 dependent variables to get one overall answer?
every last one of mine is linear, but none monotonic...what does that mean?
+Anne Go All linear relationships are monotonic, but not all monotonic relationships are linear.
Todd Grande ok thank you. ugh i wish i could show you what my matrix plot looks like.