Dear More Advanced that I R users, I am having a problem creating and interpreting some data. Here we go with the question and please let me know which parts are not clear.

I have some data that I have imported and attached with R. Lets call the data set Fun_D. Now two of the columns of the data are non- numeric data that looks like this in my data frame.

             V1OS  V2Browser
Person 1: Windows     Opera
Person 2:     Mac    Safari
Person 3:   Linux    Chrome


Where V1 is the vector of the different OS's and V2 is the vector for the different Browsers. I'v got 100 rows of data like this it doesn't stop at just 3...

Ok Now I'v got this. Finally the question. I want to see a correlation matrix (from 0-1) between the OSs and the Browsers. Say for example there are more people on the Windows OS who use Opera than on the Mac OS who use Opera, based on that we should see a higher correlation number between Windows and Opera than Mac and Opera. Does this make sense?

I'v used the Goodman and Kruskal test with some success in the past but I don't know if it is correct to use it here or how I would even interpret the results of a Goodman and Kruskal test here.

Please let me know what I can clarify as I greatly appreciate any advice you can provide,

Thank you very much



Your data is not suitable for neither ANOVA/Kruskal-Wallis nor correlation analysis. What you need is a Chi-square test for independence to determine whether the operating system is related to browser preference at all.

To study specific relations, you could then make something like a hierarchical graph (or a tree) where all OS's (level 1 nodes) are linked to all of your browsers (level 2 nodes). The weight of an edge on the graph would indicate the strength of a connection between an OS and a browser. If you represent this graph as a matrix, you can easily normalise your connection strength in the unit interval [0,1] by dividing every element in your matrix by its largest element.

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