I am working on a data set from kaggle (https://www.kaggle.com/spscientist/students-performance-in-exams) about how student performance relates to some explanatory variables, such as if the school provides lunch, gender etc.
r/dataanalysis - Which values to assign to a quantified dummy variable I have changed all the variables to quantative dummy variables and the variable I am concerned about in this post is educ_par (education parents). It can take on 6 different values, which refer to:
if both parents have a bachelors degree
if some went college
three if both of them have a masters degree
if both have an associates degree
if some have a highschool diploma
Now since, I only have dummy variables my teacher suggested me to at least include one quantitative variable. So that I can interpret it better. Here I want to change educ_par into years of education by parents. However, I run into one main problem here.
Since this is a fake dataset and the variables are not that clear I do not know what values to assign. For example, given the value 5, meaning both parents have a highschool degree, and 6, meaning only some have a highschool degree. In case with 6 I do not know what education the other parent has.Also, imagine both went to highschool, which may mean a total of 12+12= 24years of educatin by both parents, whereas if some went to college, this may mean a 15+0 years of education by both parents, since we do not know what the other parent did. In turn this could mean that assigning values like this having a highschool diploma from both parents affects the grade of their children more than if only one parent has a masters degree.
So my question is how should I quantify this variable? To not run into the problem I am facing above. May I just leave out the cases in which only some parents have a specific degree just to simplify it?
Also how does including a quantitative instead of the dummy variable effect any of my regressions? Or may they just be the same?