13 ms·
An analogous case is the programmer who relies on libraries and abstraction and "knows just enough to be dangerous." Statistics and optimization mathematics in
by coolSCV 14y ago
An analogous case is the programmer who relies on libraries and abstraction and "knows just enough to be dangerous." Statistics and optimization mathematics in particular are vulnerable to this. If you haven't read the proofs or you cannot prove it yourself, then you truly don't understand it. I'm not claiming this is you since your post doesn't imply that.
However as an example, if someone is solving linear or non-linear programs using <insert software or library here> but hasn't bothered to thoroughly study the mathematics underlying either and is just plugging in numbers from the constraint equations they came up with, then I would not want that person doing any sensitivity analysis. There would just be no way to be confident that they are interpreting the results correctly.
- cschmidt 14y agoI've benefited from lots of theoretical classes, and you're absolutely right that you need to understand the theory of what you're doing. For example, I took a lovely class from Prof. John Hooker (at CMU) that derived Linear Programming duality as a natural consequence of Farkas' Lemma, rather than just mechanically grinding through LP tableau. I certainly followed the proofs discussed in many classes. However, I can honestly say I got that understanding without doing hardly any proofs of my own. Graph theory was the only class where I "did proofs", and I didn't find it my favorite. (Later I did algorithmic graph theory and network flows - and that was fantastic, with no proofs.) I guess my point is just that an engineer can understand and use a lot of pretty advanced math without spending much effort learning about proof techniques. That certainly wouldn't be how I'd spend my time. (Of course, if you enjoy doing that then knock yourself out.)