Understanding the Difference Between P (A, B) and P (B, A)

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P(A, B) and P(B, A) represent the joint probability of events A and B occurring together, and there is no difference between them when considering the event "A and B" as identical to "B and A." Both can be expressed in terms of conditional probabilities, as shown in Bayes' Theorem. The notation P(A, B) is functional and does not depend on the order of variables unless specified. The discussion clarifies that while the expressions can be written differently, they ultimately refer to the same concept in probability theory. Understanding this equivalence is essential for applying Bayes' Theorem correctly.
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In proving Bayes' Theorem,

we use the following two statements.

P (A, B) = P (A|B) P (B)
P (B, A) = P (B|A) P (A).

I am wondering what's the difference between P (A, B) and P (B, A).

Any takers?
 
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There is no difference if by P(A,B) means the probability of the event "A and B". The event "A and B" is the same as the event "B and A".
 
Thanks!
 
failexam said:
In proving Bayes' Theorem,

we use the following two statements.

P (A, B) = P (A|B) P (B)
P (B, A) = P (B|A) P (A).

I am wondering what's the difference between P (A, B) and P (B, A).

Any takers?

P(A,B) is functional notation which is to be defined such as in f(x,y)= 6x + y^2 for example. The order of variables in the argument doesn't usually matter unless specifically stated.

You've defined it in terms of probabilities two ways which can be written:

P(A\cap B) and P(B \cap A)

They are the same but not because P(A,B) means P(A^B). P(A,B) is simply a function which is to be defined.
 
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