> concepts like "significance", "error bars", and "expected value."
Yes. I see what you're responding to--these are squarely in the statistics domain.
> not what’s realistically being covered in these high school programs.
Yes. Where the rubber meets the road. Who exiting from higher education now will have the skills to teach this imagined hybrid course? Realistically, they have to be vetted and hired by the mathematics department and satisfy some state and/or federal standards of education, which are currently staffed by educators who themselves are following standards of their office.
I was responding to the OP's premise:
> "data science" course, if designed properly, will be far more useful to students and beneficial to society than calculus.
Whether or not that objective is "realistic" given the current boundaries perscribed for high school education is another matter.
There is hope; there are modern thinkers in education out there. I referenced the UT Arlington course students and instructors referred to as DALMOOC (google it). I took this course thinking it was another data science course, and found a course taught by teachers for teachers. I hung in because their ideas were so fresh and interesting.
DALMOOC's ambition was to train teachers to encourage students to use social media to communicate their learning results, and in turn produce the data that the teachers were being traind in the course to analyze using social media analysis techniques. DALMOOC professors encouraged participants to generate social media responses to DALMOOC coursework. Very modern. Not sure how long before professors like George Siemens, whose brainchild DALMOOC was, get into state and federal positions of authority and influence to see their modern ideas at the high school level.
https://en.wikipedia.org/wiki/George_Siemens