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"It has long been an axiom of mine that the little things are infinitely the most important" (Sherlock Holmes)

#### Bayes theorem:

Let us assume that, for some event A there are n possible causes, B1 to Bn.
 For example, event A could be you finding a stray 100 note. Event Bi is that note slipping from Bundle 'i'.
You wish to know P(Bi|A), the probability that one of these causes, the ith, resulted in your observed event, A.
 (Where P(X|Y) is the probability of randomly selecting X, given Y.)

Assuming:
Each possible cause is mutually-exclusive and non-overlapping.
For each of these causes, the probability of observing A is known.
 In other words, if the kth explanation were correct, P(A|Bk) is the probability of observing A.
The probability of each causal event, P(Bi), is also known.
 If these causes are equally possible then, given n possible causes, P(Bi)= 1/n, but this is of academic interest, because they cancel out of the equation.

Then the probability that event Bi, resulted in your observed event, A, is:

 P(Bi|A) = P(Bi)P(A|Bi) P(A)
• P(A), is the probability of observing A from any of the bundles, or Σ[P(Bk)P(A|Bk)]