Assuming that photos, memory, etc. are variables (columns) in a data frame called data, then I'm afraid prop.table isn't going to work with @rensa's suggestion, either.
Here's what prop.table does: you give it a table of counts and tell it which margin(s) of the table you want to summarize over, then it converts the counts into proportions. If you give it a vector (a single list of values), it divides each value by the sum of all the values. If you combine a bunch of data frame columns into a vector using c(), then it will give you something pretty nonsensical — all the numbers from the different columns in one long list, divided by the sum of that list.
Aside: what I mean by "table"...
When you see the term "table" in this context, it doesn't mean any old information presented in columns and rows — here, it specifically means the result of cross tabulation. So in the typical case, you feed prop.table a matrix or the output from a cross tabulation function (e.g., table, xtabs).
It would help a lot to see a sample of your data and an example of the kind of table you have in mind — but in the meantime, I'm not sure I see how prop.table fits into your goals?
It sounds like you want to:
- Calculate summary stats about your dependent variable (and maybe also your covariate?)
- Fit a model? (I'm going off of "correlations among all variables" here)
- Report all this information in tabular form
But I don't know whether you're trying to figure out how to do all those steps, or if you've already done steps 1 and 2, and are just looking for a way to do 3?