Long time reader, first time writer. As the question suggests, I have a data set that contains a continuous dependent variable (exam scores, 0-50) and answers to some binary survey questions (yes it happened or no it didn't happen). The binary questions ask students what obstacles they faced when studying (work, video games, etc). So students either did, or did not, encounter that obstacle for their exam.
Using that data, I want to test the question "Does Obstacle X have any significant affect on exam score?"
The problem is that I'm not sure what statistical test(s) would be most appropriate for this combination of data. From my extremely limited understanding, it seems like many of the common tests (e.g. chi-square or Pearson's) are not correct because the data is mixture of binary and continuous.
I've considered combining the exam scores into categories (A/B/C/D/F), but have received conflicting results as to whether that is a good idea or not. I've also considered ranking the exams and trying to use some of those statistics, but my knowledge is not enough to know if that would be useful or counter-productive.
Any advice would be very much appreciated. And if I can supply any useful data or clarify anything, please let me know.