MHB Bivariate tests with dummy variables

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Bivariate tests can be conducted using dummy variables, which represent categorical data in a binary format. While dummy variables simplify analysis, they may lose some information from the original variables. Pairwise correlations can be performed by comparing combinations of dummy variables, such as geographic regions with different poverty levels. The discussion highlights a concern about the adequacy of information retained when using dummy variables for bivariate tests. Understanding the limitations and methods of analysis with dummy variables is crucial for accurate interpretation of results.
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I'm not sure if this belongs in the Basic area or here.

I have a dataset with variables that I think it makes sense to make them into dummy variables (some are categories, some are ordinal). I've been asked to do bivariate tests and regression. I don't understand how I can do bivariate tests when I'm using dummy variables.

Thanks
 
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I guess I just use the dummy variables for the bivariate tests. It just seems less than ideal because in a sense one dummy variable has less information than the original variable.

For example, if I have geographic region and poverty level, I could do pairwise correlations. region 1 with pov level 1, region 1 with pov level 2, region 1 with pov level 3, region 2 with pov level 1, etc.

I've not been able to figure out any other way to do this. Please let me know if I'm missing something.
 
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