for a task I have to predict the income ten years after A Levels from three parameters: Final high school degree (0-100%), IQ, and extraversion (scale from 0-10). I have a data set of 10000 former students, so basically a 10000x4 table with three predictor variables (degree, IQ, extraversion) and one target variable (gross yearly income).
What would be a simple way of using regression or machine learning approaches to best predict income? My idea would be that I take a subset of the students (maybe half) to determine the weights that best line up to the income. I would then use these weights to predict the income of the second half of students (an independent data set) and see how well it is doing. Does that make sense? Which functions would fit best here?