[bigger_cheese]

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.