That makes sense to me, but I’m also looking at Jayne’s in a more practical sense for social science data analysis.

I’m working through a hard copy of your book and I stumbled upon Gelman’s criticism that Jayne’s for more messy datasets (people vs physics) without objective parameters might not work well.

Gelman seems to take issue with Jayne’s in that:

1. The prior or model cannot be falsified and there isn’t enough model checking. He is more falsificationist

2. Gelman has a more frequentist definition of probability

3. Cannot change, adjust or add new priors.

4. Often impossible to know true prior…then is it ok to have a subjective one?

5. All models are wrong in social science, but some are less wrong or more useful, so important to cycle through models.

Jayne’s seems to be purist and justified, whereas gelman has pragmatic approach from practice and incorporation of other philosophies.

Since you have cited Gelman’s book, what are your thoughts on these points? The practical implication is that I’m going to be analyzing social science data, and Gelman per those dimensions seems to make more sense, but Jayne’s is more philosophically grounded.

Is your book Pure Jayne’s or would it work for a social scientist? I’m particularly interested in the idea of subjective priors incorporating theory or other non statistical experiments like ABM, falsifying and cycling through models etc

Thanks!

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http://www.stat.columbia.edu/~gelman/research/published/philosophy.pdf ]]>

Now, imagine you are looking at a similar report, where there is a ‘y’ if there is at least one girl. This is what is required to get the answer 1/3 for the version of the question without a name being mentioned.The assumptions required aren’t quite as extreme, but are still not implied by the question.

Now imagine this: You were looking at a data base of families. You recall several that caught your eye because of an unusual name. Half were boy’s names,and half were girl’s names. But the only name you specifically recall was “Florida.” Isn’t this more reasonable? This makes the answer exactly 1/2, because you must consider it equally likely that you would have noticed Florida’s brother Tex first,and recalled that.

The issue can be boiled down further than what you did. Did you notice this family because you first picked the name ‘Florida’ to be a name of interest, and sought examples? Or did the name merely catch your eye? In the first case, your conditional sample will include *ALL* families with a ‘Florida.’ In the second, it must exclude families with a ‘Florida’, but where you would have noticed her sister ‘Georgia,’ or her bother ‘Indiana’ instead. The answer is (2-f)/(4-f) in the first case, and 1?2 in the second.

Or in the simpler problem (without names), did you choose to look at only families that have a girl, or did the fact that a random family has a girl catch your eye? The answer is 1/3 in the first case, and 1/2 in the second. And one of the great things about preferring the second option, is that – as expected – the answer doesn’t change if also know the girl is a red-headed, left-handed, fan of the band U2.

I suggest you look up Bertrand’s Box Paradox, change “silver” to “bronze,” and add the obvious fourth box to complete the analogy to the two child problem. If the answer to the simpler problem, asking for the probability that both (metals, genders) match, is 1/3 when you know there is a (gold coin, girl)? Then it is also 1/3 when you know there is a (bronze coin, boy). If it is 1/3 regardless of any one (metal, gender) you know, it is 1/3 even if you don’t know a (metal, gender). But we know the answer is 1/2.

]]>” I’m looking in a report with statistical data for familes with two children. The data is not sorted in any way. The pages are filled with last names (not relevant for the riddle) and a ‘y’ if there is at least one girl with the name Florida, and a ‘n’ if there is no girl by that name. I chose an entry randomly and I see a ‘y’

I know Florida is a very rare name. What are the odds the other child is also a girl.”

There is more chance on a Florida in a two-girl family than in a one-girl family and if i see a ‘y’ the chance I’m dealing with a 2-girl family is larger.

The same can’t be said of the original problem (where it is known that at least one is a girl).

So one cannot say :”There is more chance on a girl in a two-girl family than in a one-girl family and if i see a ‘y’ the chance I’m dealing with a 2-girl family is larger” This would be nonsense to say this.