What too many people are missing is basic statistical and probabilistic concepts that allow one to evaluate and contextualize data they are constantly exposed to, and calculus isn't needed for this. Calculating the area under a distribution curve isn't nearly as important.
In my rural US curriculum, these concepts were 100% part of the (very vague) "Algebra II".
Granted it seems like it didn't stick for a large segment of folks.
(Which might be a valid thing to examine in itself: for math and science we tend to act like it's just the fact that a course is missing from the curriculum that will answer why the general population is inexperienced with it, but nearly everyone also takes composition and literature classes, and I don't feel like we can say their associated skills are really at "saturated" levels.)
Maybe I am biased because I'm an Engineer but most of the stats I do leans heavily on Calculus and Linear Algebra
A good example is regressions this is quite a common technique I rely on daily and at it certainly helps to have an understanding of slope, intercept etc.
Unfortunately my "Stats for Engineers" course at uni was not great it was pretty much focused on "this is how to interpret ANOVA output from Excel".
I've found looking at some of the more complex stats I've had to wrap my head around like Principle Component Analysis - it makes a lot more sense when you can grasp the linear algebra going on behind it.
Yes, this was how my college-level class was structured. We focused on using Matlab to plot things and understand what we were plotting as we moved across the range of topics. We never did any deep dives and no calculus and I think the class was solid (and approachable in high school with a competent instructor).
For probability, you can focus on discrete-valued random variables (this is what is covered in high schools in Poland). Don't need any calculus for that.
Good old frequentist Bernoulli and conditional probability.
The problem with it is applying it to life, which is more often Bayesian.
Sadly the high school level math can never be reasonably complete.
They should mention statistical tests and normal distribution at some point, as concepts.
cjf4|6 years ago
XaspR8d|6 years ago
Granted it seems like it didn't stick for a large segment of folks.
(Which might be a valid thing to examine in itself: for math and science we tend to act like it's just the fact that a course is missing from the curriculum that will answer why the general population is inexperienced with it, but nearly everyone also takes composition and literature classes, and I don't feel like we can say their associated skills are really at "saturated" levels.)
bigger_cheese|6 years ago
A good example is regressions this is quite a common technique I rely on daily and at it certainly helps to have an understanding of slope, intercept etc.
Unfortunately my "Stats for Engineers" course at uni was not great it was pretty much focused on "this is how to interpret ANOVA output from Excel".
I've found looking at some of the more complex stats I've had to wrap my head around like Principle Component Analysis - it makes a lot more sense when you can grasp the linear algebra going on behind it.
leetrout|6 years ago
anderspitman|6 years ago
xxpor|6 years ago
burntoutfire|6 years ago
AstralStorm|6 years ago
The problem with it is applying it to life, which is more often Bayesian.
Sadly the high school level math can never be reasonably complete. They should mention statistical tests and normal distribution at some point, as concepts.