
Randall Munroe Responds to Gelman's Criticism of XKCD - aaronjg
http://andrewgelman.com/2012/11/16808/#comment-109366
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antirez
> A sincere thank you for the gentle corrections; I’ve taken them to heart,
> and you can be confident I will avoid such mischaracterizations in the
> future!

Why Randall should almost apologize for a comic is a mystery to me.

~~~
nlh
He's not apologizing for a comic -- he's apologizing for mischaracterzing
people through his comic. He's not saying the point is wrong -- just that the
labels are :)

I think it's a thoughtful, solidly nice and totally stand-up (and mature)
thing for him to have done.

~~~
kenko
Yeah, the point is apparently just that unthinkingly accepting p = 0.05 as
your cutoff for significance is moronic (this point is utterly uncontroversial
among thinking humans), whereas the labels make it seem as if he's trying to
say something about the controversy between frequentists and bayesians, _which
he didn't even know existed_.

~~~
Osmium
> (this point is utterly uncontroversial among thinking humans)

Are you sure about this? Most people don't know any statistics, and the vast
majority of people who know _some_ statistics never took it further than Stats
101. So a lot of people _do_ blindly just apply p tests like this.

Randall's point about cancer statistics just serves to give a real world
example of this, and why it's so important people better understand it.

~~~
kenko
Well, some people might, indeed, be educated stupid, though I hope to god no
actual Stats 101 class teaches people that p < 0.05 = significant, other than
as a convention that people might want to be aware of when they encounter the
phrase "statistically significant".

I would be legitimately shocked if even a single doctor were willing to defend
that p-test as _in principle_ what it is for something to be statistically
significant _no matter what thing is at issue_ , rather than as a decent
enough heuristic.

Nevertheless, the parenthetical you highlight is, indeed, probably literally
false. I was employing a rhetorical device to convey the degree to which I
found the point that, evidently, is the one Randall _actually_ intended to be
trivial.

~~~
adrianhoward
_I would be legitimately shocked if even a single doctor were willing to
defend that p-test as in principle what it is for something to be
statistically significant no matter what thing is at issue, rather than as a
decent enough heuristic_

Unless things have changed in the last twenty years, when I did a series of
interviews with doctors about Bayesian probabilities in relation to an expert
system project, you're going to be unpleasantly surprised at both the number
who do - and the number who aren't really very sure what a p-test is at all...

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kenferry
Oh! I didn't realize this was Gelman's blog. He is, at least, a dude who
seriously knows what he's talking about.
<http://en.m.wikipedia.org/wiki/Andrew_Gelman>

~~~
pav3l
Yes, I originally started <http://news.ycombinator.com/item?id=4769667> with
title "Andrew Gelman: I don't like this cartoon", but for some reason mods
decided to get rid of "Andrew Gelman" in the title. I mean, the whole point is
that it's a _very_ famous statistician, not just another blogger ranting.

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jrockway
His name is spelled "Munroe", not "Monroe". Interestingly, the correct
spelling of his name is literally the first thing you see when you click that
link.

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gwern
LW discussion of the comic:
[http://lesswrong.com/r/discussion/lw/fe5/xkcd_frequentist_vs...](http://lesswrong.com/r/discussion/lw/fe5/xkcd_frequentist_vs_bayesians/)

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woah
Wait, hold on. Isn't the joke that the Bayesian statistician knows that paying
back 50 dollars is meaningless if the sun exploded and we're all going to die?
If we live, he gets 50 dollars. That's what I got out of it.

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hkmurakami
_> More importantly, now that both you and perhaps Scott Adams have commented
on my blog, I am very happy. If only I could think of some way of getting
Berke Breathed to comment here, I think I could just retire!_

Could someone point me to the "perhaps Scott Adams" comment? (is it in
response to another blog entry?)

~~~
1wheel
[http://andrewgelman.com/2011/04/dilbert_update/#comment-5917...](http://andrewgelman.com/2011/04/dilbert_update/#comment-59176)

~~~
hkmurakami
Thanks! :)

(Now I see why it's _perhaps_ Scott Adams)

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wisty
AFAIK, the breakdown is this:

Frequentist is a special case of Bayesian. The Frequentists have much more
mature tools, because they've been working on them since Gauss's day.
Bayesians (especially less experienced ones) may claim that that Frequentists
are old school, outdated, and don't teach undergrads the new Bayesian way of
doing things.

Bayesian methods are more flexible and general, but are often slow
(computationally), and can be too flexible. A Bayesian can prove anything.
Frequentists have trouble eliminating some biases (because their tools aren't
as flexible), but also have trouble purposely (or subconsciously) biasing
their results.

I'm not going into the specifics of the methods here, just the source of their
disagreements.

~~~
dbecker
Almost everything written here is incorrect.

First of all, Bayes predates Gauss. It is inaccurate to suggest frequentist
statistics predate Bayesian statistics.

Second, neither is a special case of the other.

Third, neither Bayesian methods nor frequentist methods are inherently "more
flexible."

Bayesian statistics set up a model and infer model parameters by applying
Bayes' rule to the data. Bayes' rule is an indisputable rule of probability.

For any model parameter b, the result of applying a bayesian model is a
probability distribution for b given the available data. Criticisms of
bayesian models typically center around the fact that you must use a "prior
distribution" indicating the modeler's beliefs about b before seeing the data.
Bayesian statisticians have a number of responses to this criticism (that some
people find compelling, and others do not).

Frequentist methods build models that are justified by their properties in
repeated resampling. For instance, a frequentist method is "unbiased" if,
given multiple hypothetical samples, it would on average produce the correct
parameter b. Frequentist hypothesis testing reports the probability of
observing specified data given some assumption about b.

A standard criticism of frequentist methods is that a modeler wants a
probability distribution for an unknown parameter given the known data...
rather than knowing the probability of observing the realized data given some
assumption about the parameter.

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bashzor
I love this line.

 _The truth is, I genuinely didn’t realize Frequentists and Bayesians were
actual camps of people—all of whom are now emailing me._

~~~
noonespecial
He should be doubly cautious of Rule 34 in this case.

<http://xkcd.com/305/>

~~~
anonymfus
How viewer must recognize who are Frequentists and Bayesian in porn? Of course
it possible to place tattoos with formulas on bodies or put some blackboards
in background (conventional plot about student and teacher?), but can it be
more elegant? May be some joke about contraception?

