Re: The Promise of Forth

John Doty <jpd@xxxxxxxxxxxxxxxxxxxxxxx> wrote:
Jonah Thomas wrote:
John Doty <jpd@xxxxxxxxxxxxxxxxxxxxxxx> wrote:
Jonah Thomas wrote:
John Doty <jpd@xxxxxxxxxxxxxxxxxxxxxxx> wrote:
Jonah Thomas wrote:

What would we do to test which of these was true?

My problem here is that it appears we have only one history to
go>>>> by, and we can't do very good statistics on that.
In astronomy we're quite used to using statistics to examine
historical data. We're not the only ones, either: consider
epidemiology. What's needed, though, is a quantitative
statistical>>> theory.

If people at a church picknick get food poisoning and you want to
figure out what did it, you can look at each different food and
ask>> who ate it. You might get a graph like this

chicken egg salad mashed potatoes waldorf salad

ate&gotsick 56 34 30 55
ate&well 62 37 38 35

none&sick 8 30 27 0
none&well 10 30 31 32
132 131 126 132

Incidentally, consider what sort of statistics you'd do about this?
Lots of people eat contaminated food and don't get sick, so when you
look at what people ate you don't get a smoking gun. Lots of
correlation between eating the spoiled food and the unspoiled food.
Not very good statistics at all. And the data isn't perfect, either.
But if only one kind of food is spoiled you can look at the people
who didn't eat it and who got sick anyway. This time it's almost
certainly the waldorf salad, because all 32 people who didn't eat it
didn't get sick.

The table is so scrambled I couldn't see that. But that's perfectly
analyzable statistically. Since otherwise it seems to have been about
50/50, the probability of 0/32 is roughly 1 in 4 billion (heads come
up 32 times in a row). The null hypothesis is therefore ruled out at
that level. This could be done more carefully, but it hardly matters.

If you look at 56:62 and 34:37 and 30:38 and 55:35 then the waldorf
salad looks a bit more likely but nothing to be sure about.

If you look at 8:10 versus 0:32 then it isn't statistical. Everybody who
got sick had eaten the waldorf salad. For each other item there were
people who didn't eat it who got sick, but not for the waldorf salad. 56
people with food poisoning at the picnic implies they ate something that
was bad. If it was one item and not two, then the bad one had to be the
waldorf salad.

It doesn't take much
statistics. When this sort of problem is muddy enough for statistics
to be useful you probably won't find much of an answer.

On the contrary, in real life it's almost always that muddy, and
statistics are necessary.

Sometimes logic works.

No professional epidemiologist would use logic here. Believe me, I'm
married to one.

Ask her to explain it to you, then.

But what data do we have about Forth to do quantitative statistics
on?
We don't. That's why we can't address a statistical hypothesis.

Then you have no basis to rule out the null hypothesis. You're going
on gut instinct.

No, I'm going by the usual rule that an untestable hypothesis is not
admissible in science. Bayes' theorem tells you that, in fact, it's
when you admit an untestable hypothesis you're going on gut instinct,
because the likelihood you get back simply reflects your "prior"
("prejudice" in more colloquial English).

If you can show that your hypothesis fits better than the null
hypothesis does, then you have something. You're telling us that your
hypothesis is untestable.

Why should we argue about this? Why not look at what you want to
accomplish and possible ways to do it, rather than keep arguing that the
historical pattern of events was inevitable? Sure, it isn't just
marxists who believe in historical determinism, but we don't need to
keep arguing about that do we, when the more interesting question is how
to improve Forth....
.

Relevant Pages

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