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JeffJo comments on Probability is in the Mind - Less Wrong

60 Post author: Eliezer_Yudkowsky 12 March 2008 04:08AM

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Comment author: JeffJo 15 June 2013 07:29:25PM 0 points [-]

Since this discussion was reopened, I've spent some time - mostly while jogging - pondering and refining my stance on the points expressed. I just got around to writing them down. Since there is no other way to do it, I'll present them boldly, apologizing in advance if I seem overly harsh. There is no such intention.

1) "Accursed Frequentists" and "Self-righteous Bayesians" alike are right, and wrong. Probability is in your knowledge - or rather, the lack thereof - of what is in the environment. Specifically, it is the measure of the ambiguity in the situation.

2) Nothing is truly random. If you know the exact shape of a coin, its exact weight distribution, exactly how it is held before flipping, exactly what forces are applied to flip it, the exact properties of the air and air currents it tumbles through, and exactly how long it is in the air before being caught in you open palm, then you can calculate - not predict - whether it will show Heads or Tails. Any lack in this knowledge leaves multiple possibilities open, which is the ambiguity.

3) Saying "the coin is biased" is saying that there is an inherent property, over all of the ambiguous ways you could hold the coin, the ambiguous forces you could use to flip it, the ambiguous air properties, and the ambiguous tumbling times, for it to land one way or another. (Its shape and weight are fixed, so they are unambiguous even if they are not known, and probably the source of this "inherent property.")

4) Your state of mind defines probability only in how you use it to define the ambiguities you are accounting for. Eliezer's frequentist is perfectly correct to say he needs to know the bias of this coin, since in his state of mind the ambiguity is what this biased coin will do. And Eliezer is also perfectly correct to say the actual bias is unimportant. His answer is 50%, since in his mind the ambiguity is what any biased coin do. They are addressing different questions.

5) A simple change to the coin question puts Eliezer in the same "need the environment" situation he claims belongs only to the frequentist: Fli[p his coin twice. What probability are you willing to assign to getting the same result on both flips?

6) The problem with the "B9" question discussed recently, is that there is no framework to place the ambiguity within. No environmental circumstances that you can use to assess the probability.

7) The propensity for some frequentists to want probability to be "in the environment" is just a side effect of practical application. Say you want to evaluate a statistical question, such as the effectiveness of a drug. Drug effectiveness can vary with gender, age, race, and probably many other factors that are easily identified; that is, it is indeed "in the environment." You could ignore those possible differences, and get an answer that applies to a generic person just as Eliezer's answer applies to a generic biased coin. But it behooves you to eliminate whatever sources of ambiguity you easily can.

8) In geometry, "point" and "line" are undefined concepts. But we all have a pretty good idea what they are supposed to mean, and this meaning is fairly universal.

"Length" and "angle" are undefined measurements of what separates two different instances of "point" and "line," respectively. But again, we have a pretty clear idea of what is intended.

In probability, "outcome" is an undefined concept. But unlike geometry, where the presumed meaning is universal, a meaning for "outcome" is different for each ambiguous situation. But an "event" is defined - as a set of outcomes.

"Relative likelihood" is an undefined measurement what separates two different instances of "event." And just like "length," we have a pretty clear idea of what it is supposed to mean. It expresses the relative chances that either event will occur in any expression of the ambiguities we consider.

9) "Probability" is just the likelihood relative to everything. As such, it represents the fractional chances of an event's occurrence. So if we can repeat the same ambiguities exactly, we expect the frequency to approach the probability. But note: this is not a definition of probability, as Bayesians insist frequentists think. It is a side effect of what we want "likelihood" to mean.

10) Eliezer misstated the "classic" two-child problem. The problem he stated is the one that corresponds to the usual solution, but oddly enough the usual solution is wrong for the question that is usually asked. And here I'm referring to, among others, Martin Gardner's version and Marilyn vos Savant's more famous version. The difference is that Eliezer asks the parent if there is a boy, but the classic version simply states that one child is a boy. Gardner changed his answer to 1/2 because, when the reason we have this information is not known, you can't implicitly assume that you will always know about the boy in a boy+girl family.

And the reason I bring this up, is because the "brain-teasing ability" of the problem derives more from effects of this implied assumption, than from any "tendency to think of probabilities as inherent properties of objects." This can be seen by restating the problem as a variation of Bertrand's Box Paradox:

The probability that, in a family of two children, both have the same gender is 1/2. But suppose you learn that one child is in scouts - but you don’t know if it is Boy Scouts or Girl Scouts. If it is Boy Scouts, those who answer the actual "classic" problem as Eliezer answered his variation will say the probability of two boys is 1/3. They'd say the same thing, about two girls, if it is Girl Scouts. So it appears you don’t even need to know what branch of Scouting it is to change the answer to 1/3.

The fallacy in this logic is the same as the reason Eliezer reformulated the problem: the answer is 1/3 only if you ask a question equivalent to "is at least one a boy," not if you merely learn that fact. And the "brain-teaser ability" is because people sense, correctly, that they have no new information in the "classic" version of the problem which would allow the change from 1/2 to 1/3. But they are told, incorrectly, that the answer does change.