Re: Pizza Example
Date: Wed, 07 Apr 2004 11:40:11 GMT
"Anthony W. Youngman" <wol_at_thewolery.demon.co.uk> wrote in message
> In message <yRzcc.51347$9b1.1688_at_newssvr16.news.prodigy.com>, Eric Kaun
> <ekaun_at_yahoo.com> writes
> >"Anthony W. Youngman" <wol_at_thewolery.demon.co.uk> wrote in message
> >> Somebody gave me a wonderful quote recently. "Logic and mathematics
> >> you a consistent model. Academicians have an unfortunate tendency to
> >> confuse consistency with truth."
> >It's an interesting quote, but I'm not so confused. Fine - consistency
> >truth, and let's assume that it doesn't even imply truth. How would you
> >judge the "truth" of a model? Such doesn't even make sense, really.
> >are useful or not. Consistency is one of the best measures we have, but
> >doesn't mean it's perfect. Out of curiosity, how do you judge a model?
> How do I judge a model? Simple, really. How good a match to reality is
> it? As a scientist, can I use it to predict the future?
That just begs the question - who's judging the match to reality? This simply gets into the entire application-view versus business-view argument again: an application programmer is going to see a thin slice of reality, as reflected in application requirements. Someone else sees a different view, with some overlap.
In the physical sciences it's much easier to judge the validity of a model, since we can measure physical reality and compare with predictions made by the model. Information systems don't have analogous concepts to prediction and physical reality, since people are defining their business reality (often as they go along).
I don't think Newtonian Mechanics is a mathematical theory. Isn't it a model?
> if I try to predict where Mercury will be in a year's time, using
> Newtonian Mechanics, I am going to get it embarrassingly wrong.
> What is important is knowing which models are appropriate, and when - I
> would perfectly happily use Newtonian Mechanics to calculate the orbit
> of Venus ... it's just that I know the answer will not be perfect. And
> while the error is insignificant for Venus, it's very noticeable for
I'm going to take another crack at this later, since I got little sleep and am very tired, but the analogies between data models and physical scientific models are just wrong, comparing apples and hockey pucks. But I lack the eloquence to explain it right now - maybe someone else could chime in.
> >Hmmm. In other words, you assume that you, your significant other, or
> >garbageman are equally adept at performing a quintuple bypass, or perhaps
> >walking a tightrope 20 stories up on a windy day or cleaning a nuclear
> Actually, while I couldn't do any of those three, I do happen to
> understand the theory behind them. And certainly with regard to
> "cleaning a nuclear reactor", I would expect I understand it a damn
> sight better than the person doing it - he's probably an underpaid
> "monkey" (no disrespect meant - but they pay peanuts, what do they
> expect?) following a procedure by rote.
Sorry, I apparently got us off on a tangent here, and won't continue to argue this point...
> As regards practical ability, I would agree with you - I don't practice
> my trombone enough :-) But as regards *UNDERSTANDING*, I would disagree.
> Most people either have the intelligence to do so and quickly, or they
> struggle and never get there.
So let me get this straight: most people have either the intelligence to understand anything quickly, or don't have the intelligence to ever understand anything? I don't know who you've been hanging around with, but they sound interesting. Or boring. One or the other.
> DO I trust the experts who designed this infernal machine? I have a
> pretty decent grasp of the theory. So I don't need to. I can (should I
> wish to) check it out for myself. And if something "feels wrong" I
> nearly always do.
That has nothing to do with trust - just troubleshooting. You're still using the thing because it works most of the time. But again, I got us off on a tangent...