I've recently been tasked with an Data Science interview assignment and looking over the variables, I wondered if it is professionally acceptable to make a new independent variable out of old ones (or at least modify the independent variables in a way to potentially get more worthwhile data).
For example, one of the variables has data on a person's birth state/territory. So instead of trying to model using 50+ categories, creating a new variable that would categorize each state by region (North East, Midwest, South, Etc.) might lead to more significant and easier to interpret analysis.
I know the objective, or what we're trying to answer, is important, but I wonder if making brand new variables or significant changes like this is appropriate for an interview assignment?