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- TL;DR Summary
- If we have two identical data sets that were generated by different processes, will their statistical weight as evidence for or against a hypothesis be different?
The specific example I'm going to give is from a discussion I am having elsewhere, but the question itself, as given in the thread title and summary, is a general one.
We have two couples, each of which has seven children that, in order, are six boys and one girl (i.e., the girl is the youngest of the seven). We ask the two couples how they came to have this set of children, and they give the following responses:
Couple #1 says that they decided in advance to have seven children, regardless of their genders (they think seven is a lucky number).
Couple #2 says that they decided in advance to have children until they had at least one of each gender (they didn't want a family with all boys or all girls).
Suppose we are trying to determine whether there is a bias towards boys, i.e., whether the probability p of having a boy is greater than 1/2. Given the information above, is the data from couple #2 stronger evidence in favor of such a bias than the (identical) data from couple #1?
We have two couples, each of which has seven children that, in order, are six boys and one girl (i.e., the girl is the youngest of the seven). We ask the two couples how they came to have this set of children, and they give the following responses:
Couple #1 says that they decided in advance to have seven children, regardless of their genders (they think seven is a lucky number).
Couple #2 says that they decided in advance to have children until they had at least one of each gender (they didn't want a family with all boys or all girls).
Suppose we are trying to determine whether there is a bias towards boys, i.e., whether the probability p of having a boy is greater than 1/2. Given the information above, is the data from couple #2 stronger evidence in favor of such a bias than the (identical) data from couple #1?