Yes, every text used its own conventions for variable names, different words to say the same thing, etc, but no, that wasn't a problem (for me at least). I thi

Yes, every text used its own conventions for variable names, different words to say the same thing, etc, but no, that wasn't a problem (for me at least). I think the point I was trying to make (not so well) is that perhaps it's not that programmers do not like math, but rather that when you learn to view everything through a programmer's eyes, i.e. "how am I going to actually build this damn thing", you tend to get very wary of abstract or generic approaches which is what scientific books are made of. For example, if I were given a book with a chapter on Holt-Winters and told that there'd be a quiz later, I could have "mastered" it in a night probably. But when I had to write the code to actually do that, I'd find out that this book does not mention how you come up with initial values, while wikipedia does, wikipedia cites this NIST publication, but who wrote that and is it any good? Then I came across a 2014 paper that says that the forecast can be improved with a slight change in one of the formulas, only when I tried it, my results were worse; no book mentioned how to find best alpha, beta and gamma, because for that you need some kind of a gradient descent or nelder-mead method, and on and on. _That's_ what took months (and it was challenging and fun too), and I think we agree that there isn't a solution to this, it's a dilemma, not a problem. (As someone once said - avoid trying to solve dilemmas and avoid managing problems).