Intersection of two independent events

In summary, the conversation discusses the relationship between two independent events A and B and how it affects their joint probability. It explains that the sample space for these events is the Cartesian product of their individual spaces, and that the independence of the events allows for a simplified calculation of their joint probability.
  • #1
Avichal
295
0
If A and B are two independent events then P(A intersection B) = P(A).P(B)
I don't refute this but it confuses me. What is the sample space in this?
For eg: - If A is the event that we get Head while tossing a coin and B is the event that we get 2 while throwing a die, then what will we be the sample space? Is it {H, T} or {1, 2, 3, 4, 5, 6}?
 
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  • #2
Hey Avichal.

If you have two sets A and B that are independent, then the state space for all combinations is the Cartesian product C = A X B (a belonging to A, B belonging to b, c = (a,b) belonging to C).

With regards to independence, the way you get the definition is the following:

P(A|B) = P(A and B)/P(B) [definition of conditional probability].

If A is independent from any other random variable then P(A|B) = P(A). This implies:

P(A|B) = P(A) = P(A and B)/P(B). Multiplying everything by P(B) gives

P(A and B) = P(A)*P(B) and thus proved.
 
  • #3
Hmm ... If A and B are dependent then P(A|B) = P(A and B) / P(B)
Here what will be the sample space? For B it will be different compared to A and B. So how does it work?
 
  • #4
The sample space is the direct product space, i.e. the elements are {h,1}, {t,1}, {h,2}, etc.
 
  • #5
chiro said:
If you have two sets A and B that are independent, then the state space for all combinations is the Cartesian product C = A X B (a belonging to A, B belonging to b, c = (a,b) belonging to C).
Hi Chiro,
I think that's a bit confusing. Perhaps you meant this:
If you have two sets A and B that are subsets of apparently unrelated event spaces Ω1, Ω2, then in order to discuss joint probabilities etc. you must first combine the event spaces. Given their independence as spaces (not to be confused with independence of events within a space), the appropriate combination is the Cartesian product ΩC = Ω1 X Ω2. Each space has its own probability function, but they are related. A ⊂ Ω1 maps naturally to A X Ω2 ⊂ ΩC. P1(A) = PC(A X Ω2) etc. Now we can understand the joint event "A and B" as (A X Ω2) ∩ (Ω1 X B) = A X B.
 
  • #6
I was only talking about the event space without reference to a probability measure. The measure and filtration/sigma-algebras come on top of this, but I wasn't really getting specifically into this (as you have).

This was just a way to say that if you can have every permutation of possibilities from both sets, then the cartesian product will give you a state-space that describes such possibilities.

Applying zero probabilities or other constraints is further step on top of this.
 

Related to Intersection of two independent events

1. What is the definition of "intersection of two independent events"?

The intersection of two independent events refers to the outcome of an experiment or situation where two events occur simultaneously, but have no influence on each other. In other words, the occurrence of one event does not affect the probability of the other event occurring.

2. How is the intersection of two independent events calculated?

The intersection of two independent events is calculated by multiplying the probabilities of each event occurring. For example, if the probability of event A occurring is 0.5 and the probability of event B occurring is 0.3, then the probability of both events occurring simultaneously would be 0.5 x 0.3 = 0.15.

3. Can the intersection of two independent events ever have a probability greater than 1?

No, the intersection of two independent events can never have a probability greater than 1. This is because the probability of an event occurring can never exceed 1, and when calculating the intersection of two events, we are essentially multiplying their probabilities together.

4. How is the intersection of two independent events related to the concept of independence?

The intersection of two independent events is closely related to the concept of independence. If two events are independent, it means that the outcome of one event does not affect the probability of the other event occurring. Therefore, the probability of the intersection of these events will simply be the product of their individual probabilities.

5. Can two events be considered independent if their intersection has a probability of 0?

Yes, two events can still be considered independent even if their intersection has a probability of 0. This is because the definition of independence is based on the events having no influence on each other, rather than the probability of their intersection being non-zero.

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