That was my thought too, to make a simplistic example if a university had both say an engineering school and an art school, it might presumably do worse than a university with only an engineering school. So this metric might favor smaller, focused schools which happen to concentrate on education areas with high median salaries...

> So this metric might favor smaller, focused schools which happen to concentrate on education areas with high median salaries...

I don't think that part's necessarily true. If a school focuses on an area with high median salaries, the model will take that into account in the predicted salaries, so the school will have to have even higher actual salaries than typical for the field (and its input demographics, SAT scores, etc.) to get a positive value-add. See Caltech for an example of a STEM-focused school that does badly by this measure: from its SAT scores, demographics, and heavy concentration of STEM majors, the regression analysis predicts that it should produce graduates with a median salary of $82k. But the actual median is $74k, so its value-add is taken to be -$8k.

Some of the schools that do well are in areas with poor salaries, but score highly because they do better than you'd expect (or than the model would expect, anyway) for that area and student demographics. Otis College of Art and Design has a predicted salary of $29k from the regression analysis, but actual median is $42k, so implied value-add +$13k.

Interestingly, having gone to Caltech, I suspect that its extreme focus on STEM research actually hurt it here. Mostly because that focus results in a very large portion of undergrads going on to grad school (much larger % than any other university), and grad students don't earn very much.

Hi there, Mike! Care to expound on any solutions to make Tech more industry oriented? Are there things you'd rather have been exposed to more in your undergrad education given where you're at now?

Not all the majors at Caltech are going to be value adds, and of those that are, they are generally leading to bench/engineering rather than business dev/marketing/executive positions

It assumes you select a school that is focused on your field of choice, so if you pick an art school, your preference is for art, and if you pick an engineering school, your preference is for engineering.

The issue is that you can't select the University of Washington's engineering school. You can only see University of Washington which has both an engineering and an art school, and so it doesn't tell you what the data will be if you only look at engineering students.

Here is another way to see the expectation of the students by state - https://tuvalabs.com/benf/datasets/s/fdcbab1d15e64518a3cc3a5...

any time data is shown in the article, it should be best to provide access to raw data as anyone can analyze with their own angle. When I see static graphs and analysis I smell distorted facts. (of course in this case you can do search, but giving access to raw data would be more useful.)