Assessing Chance of Donation with Bayes Law

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Homework Help Overview

The problem involves using Bayes' law to determine a posterior distribution regarding the likelihood of a man donating to charity based on prior observations of his donation behavior over the past two years. The subject area is probability theory, specifically Bayesian inference.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the formulation of the posterior distribution P(x|observation) and the components involved, including the prior distribution and the likelihood of observations. There is an exploration of sequential versus non-sequential approaches to the problem.

Discussion Status

Some participants have offered guidance on the steps to take in applying Bayes' law, emphasizing the importance of considering the sequential nature of observations. Others have noted the possibility of alternative approaches to compute the posterior distribution.

Contextual Notes

There is mention of the need for normalization in the calculations and the potential confusion arising from the sequential nature of the observations. Participants are encouraged to clarify their understanding of the setup and the implications of their assumptions.

mimsy57
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Homework Statement


Each year, a man will donate money to a charity with chance x [0,1] (chosen the first time he donated, and not changing), with the prior distribution P(x)=x^3+2x-1/4. Use Bayes law to find a posterior distribution given these observations and help the charity determine if they should expect a donation this year, given that he donated both of the last two years.

Homework Equations


P(x|observation)=P(observation|x)*P(x)/P(observation)

The Attempt at a Solution


I have no samples to go off of, so just hoping someone can tell me if I have the right idea:

I want to find P(x|observation) first and then the expected value of P I think. To find P(x|observation) I will do:

P(observation|x)=x^2 (because he donated twice, and P(donation)=x)
P(x)=x^3+2x-1/4 (prior distribution given)
P(ovservation)=∫(f(x)^2) from 0 to 1 (because we need the unconditional probability that f(x)=x.

Is my understanding of the above pieces correct?
 
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if ##Y## is the event that a man donates to charity, then $$p(y|x) = x$$ ... I think you've got that right.

I think you need to take it slowly - one step at a time: it's kind-of an odd thing to ask. How on Earth would this situation get set up in the first place? But it's an exercise.

After the first observation the posterior is: $$p(x|y)=\frac{1}{p(y)}p(y|x)p(x)$$ ... p(y) is determined by normalization of the rest.

After the second observation the posterior is: $$p(x|y,y)=\cdots$$ ... write the whole thing out in symbols without anticipating their values - don't forget that the new prior is going to be the old posterior.

[note, if the third observation was no charity donation, then the posterior is ##p(x|y,y,\neg y)##]

reference: http://home.comcast.net/~szemengtan/InverseProblems/chap5.pdf
(note-I've munged the notation a bit since y is boolean)
 
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Thanks! I was totally missing the sequential nature.
 
mimsy57 said:
Thanks! I was totally missing the sequential nature.

You can also do it non-sequentially; that is, you can regard your 'observation' as 'two donations in two years', and then compute the posterior. In other words, you get the same thing if you do it in either of two ways (but correctly each way):
(1) \text{ prior} \to \text{obs. 1} \to \text{post. 1} \to \text{obs. 2} \to \text{post. 2} \\<br /> (2) \text{ prior} \to \text{obs. 1 and obs. 2} \to \text{post. 2}
 
Yah - it's just that if you get confused like that, it is best to go by little steps.
 

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