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Suppose you had information of a true success rate of passing an exam from different schools, and that the 'true' success rates are similar, can you assume exchangeability is applicable to these values, or is there not enough info to assume it?,if so, then what more info is needed to make a reasonable assumption?

Also, since the values are considered similar, what would be a logical way to estimate the success rate at a say 5-th school given you have values of the true success rate from 4 schools already, is it just a simple average? I'm not sure whether the concept of exchangeability can be applied here, and generally not getting how it can be applied to similar situations, involving a sequence of numbers.

s.stats
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    I highly welcome questions about exchangeability. But could you please provide a clear and simple practical example. It could look something like: exam A on matter B in school C sees 90/100 students pass, etc. What exactly are you after? Comparing success rates? Between schools? What is your understanding of exchangeability? Link to the relevant wiki. It will greatly help your question. – Jim Apr 16 '18 at 22:08
  • say the success rate in passing is 50%,75%,66% and 80% amongst 4 schools within a county in England, under what circumstances would you assume exchangeability? I am familiar with De fenetti's theorem and the general definition of exchangeability. I think exchangeability applies here as the rates in schools within a county can be assumed to be similar, and the rates seem somewhat close. – s.stats Apr 16 '18 at 22:43
  • Also, to predict the 5-th school, would it be reasonable to assume a beta prior, calculate the params through mean and variance of rates, or is there an alternative to this, based on intuition? – s.stats Apr 16 '18 at 22:44
  • Just trying to make sense of exchangeability in a practical setting in relation to hierarchical models. Also, not seeing how the definition of exchangeability follows from De fenetti's theorem or the other way around? The definition implies that the rates would have the same marginal distribution(I think), but what is the link between that and what De fenetti theorised? Just confused all round.Thanks
  • – s.stats Apr 16 '18 at 22:53
  • Okay. Any reasons not to assume independence? – Jim Apr 16 '18 at 22:54
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    Ah right, so if we assume independence that implies exchangeability. – s.stats Apr 16 '18 at 22:57
  • What about in the case we can't assume independence? – s.stats Apr 16 '18 at 22:57
  • Just so you know: I’m not commenting to critique. But simply to get your question into a form in which it is most likely to receive a good answer. :) – Jim Apr 16 '18 at 23:00
  • @s.g.: Just ask yourself if you have any information about the schools (other than the pass rates) distinguishing between them. Are some in very poor neighborhoods, others not? ... independence is in a way much stronger than exchangeability, so is not a good way to argue. – kjetil b halvorsen Dec 30 '18 at 20:59
  • More examples at https://stats.stackexchange.com/questions/353722/exchangeability-of-group-effects/353739#353739 – kjetil b halvorsen Jan 03 '19 at 22:18