What type of correlation analysis should I use?

So I made a questionnaire with one part being sort of a quiz with right and wrong answers, along with "Don't Know" answers. I took all these, recoded them so that the right answers are 1 and the others are 0. After that, I used Compute to give out: right answers/total # questions. There are 13 questions so if people get 12 out of 13, then they got a .92. Anything that's .50 and below would mean they have little to no knowledge on the subjects being discussed.

One of my hypotheses is about a significant relation between the individual's political party identification and their knowledge (here we have the knowledge questions on the "quiz".

Now, the party variable is categorical. The sample is asked if they identify with Party A, Party B, Party C, Non-partisan or Other. My sample chose mostly A, B, and Non-partisan, with the other options receiving really low scores. So I imagine I would mostly have to use the first two.

Which correlation analysis should I use? In my class, we talked a lot about Pearson and Spearman correlations, along with Chi-Square and others. However, I am not sure how to look for any correlation between Party ID and their knowledge. Another professor suggested t-test if I'm looking for a significant relation between party ID (if any) and the individual's knowledge.



TS Contributor
You can use t-test (if you include only 2 groups) or oneway ANOVA (three groups). Or, if your sample size is small, or your dependent variable is to be considered ordinal (e.g. most people have only 5 or 6 corrects answersat best), then you could try Mann-Whitney U-test (2 groups) or Kruskal-Walis H-test (3 groups).

With kind regards