The original project involved giving different forms of instruction to three different groups. We also gave participants a questionnaire regarding previous knowledge of the subject, how many college courses they've taken, and how much they liked the instruction formats. Because of group randomization, things like previous experience and courses taken shouldn't be significant between groups, but opinions about the instruction format and its effectiveness may be. There are 15 questions total, many of which are interrelated (e.g., how many psych courses taken and how many graphs a student has made may be correlated because of course assignments to make graphs).
How should I test for differences between groups on these questions? I thought I might use a separate ANOVA for each question, then use a Bonferroni correction to protect from familywise error, but is there a simpler, more powerful, or more common way?
Thanks for the help!
How should I test for differences between groups on these questions? I thought I might use a separate ANOVA for each question, then use a Bonferroni correction to protect from familywise error, but is there a simpler, more powerful, or more common way?
Thanks for the help!