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Bayes law

  1. Nov 9, 2008 #1

    This question relates to Bayes law. I think my problem is im not sure of the name of the thing im trying to derive...

    I have 2 variables a and b.
    a = 1 or 0, b = 0...n
    I have the data to calculate;
    p(a = 1 and b) p(b)
    for any b. Hence I can find p(a=1|b) = p(a = 1 and b)/p(b)

    What I want is p(a=1|b), but 'given' that a = 1. I dont want this to be affected by p(b), hence im not trying to find p(b|a=1).
    To explain further what i mean; If event a = 1, what is the prob it will happen at a certain b, independant of the frequency of occurences of different b's.

    So I normalise;
    [tex]\sum_{b = 0}^n p(a=1|b).N = 1[/tex]

    Where N is a constant.

    [tex] N = \frac{1}{\sum_{b = 0}^n p(a=1|b) }[/tex]

    [tex] p(a=1,b) = \frac{p(a=1|b)}{\sum_{b = 0}^n p(a=1|b)}[/tex]

    is that alright and does it have a name???

    Many thanks in advance for any advice...

  2. jcsd
  3. Nov 11, 2008 #2
    According to Bayes' Law p[a|B]p = p[a,B] = p[B|a]p[a]; in order for your formula to be Bayesian it must conform with this.

    I would definitely have logged in as EnumaElish had PF administration awarded that account the privilege of posting replies, after I reset my e-mail address Tuesday, October 28, 2008.
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