Without going into specifics, I'm currently working on a system that involves 20-25 questions being answered as either Green, Yellow, Orange or Red. After completing a subset of these questions (many questions can be left as defaulting to Green), the system allows our users to choose one outcome out of four, roughly corresponding to the answers they entered (OutcomeGreen, OutcomeYellow, OutcomeOrange or OutcomeRed). The answer that was selected most tends to be a good indicator as to what outcome they will select, but that's not always the case.
After having this system in place for the last 2 years, now I've received a request to have the system itself make a recommendation as to which outcome the user should select. Using data already accumulated over this period, I'd like to get some insight as to which questions/answers tend to be most influential for specific outcomes, and possibly give them more weight when determining what to recommend.
My main dilemma is that my last class on statistics was more than 20 years ago, and just looking through the tags here made me feel that I'm out of my depth. With the description I've provided, and the vast knowledge contained within this SE:
- Is there anything I should be looking into (tools, subset of CrossValidated tags) that would help gain better insight, and where I should look for more information?
- Is there a quick way to get up-to-speed on what I'm missing?
Background: I'm a developer in many programming languages, and an amateur mathematician (mostly playing around in number theory and linear programming). I'm also a quick learner; I've been learning how to use R in my spare time. I just need some indication as to where I would find info quickly that would help me move forward with this.