If O is an event space, show for a finite number of events--

In summary, this problem can be solved by finding a k-element set in ##B_k## that is not in any other k-element set."In summary, the set of points in the event space which belong to exactly k of the A_i's in O belongs to O.
  • #1
Eclair_de_XII
1,083
91

Homework Statement


"If ##A_1,...,A_m\in O## and ##k\in ℕ##, show that the set of points in ##Ω## (the sample space) which belong to exactly ##k## of the ##A_i## belongs to ##O## (the previous exercise is the case when ##m=2## and ##k=1##)."

Homework Equations


Event space: O
##O\neq ∅##
##\text{If} \space A\in O\space \text{then} \space Ω\cap A^c \in O##
##\text{If} \space A_1,...\in O \space \text{then} \space \bigcup_{i=1}^\infty A_i \in O##

The Attempt at a Solution


This is how I have done the case for when ##m=2## and ##k=1##:

Since ##A,B\in O##, then it follows that since ##O## is closed under the operations of finite unions, that ##A\cup B\in O##. Moreover, since ##O## is closed under the operations of finite intersecctions, then it is true that ##A\cap B \in O##. Moreover, since ##A\cap B \in O##, then ##Ω\cap (A\cap B)^c \in O##. In turn, the symmetric difference of ##A## and ##B##, ##(A\cup B)\cap (A\cap B)^c =AΔB\in O##.

This is my attempt to solve for ##m,n\in ℕ##:

Since ##A_i\in O, i\in [1,m]\ \cap ℕ##, then it follows that ##\bigcup_{i=1}^m A_i \in O##. Moreover, ##\bigcup_{i\neq j} A_i\cap A_j\in O##. Then ##(\bigcup_{i=1}^m A_i)\cap (\bigcup_{i\neq j} A_i\cap A_j)^c\in O##. I've tried defining a set ##B_j=\{A_i:\forall x,y\in Ω, \text{If} \space x\in A_i, y\in A_n, \text{then} \space x,y\notin A_i\cap A_n, n\neq i\}##, with ##1\leq j \leq k## and writing: ##(\bigcup_{j=1}^k B_j)\cap (\bigcup_{i\neq j} A_i\cap A_j)^c\in O##, but I'm not really sure that I understand the problem.
 
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  • #2
Eclair_de_XII said:
"If ##A_1,...,A_m\in O## and ##k\in ℕ##, show that the set of points in ##Ω## (the sample space) which belong to exactly ##k## of the ##A_i## belongs to ##O## (the previous exercise is the case when ##m=2## and ##k=1##)."
Call the set described in red text ##B_k##.

Now for ##k\in\{1,...,m\}## define ##D^m_k## to be the set of all ##k##-element subsets of ##\{1,...,m\}##. Then the set of all elements that are in ##k## or more of the ##A_j## is
$$F_k\triangleq \bigcup_{S\in D^m_k} \bigcap_{j\in S} A_j$$
Confirm this to yourself before proceeding.

Then confirm that ##F_k\in O##.

Then see if you can write ##B_k## as the result of a finite sequence of sigma-algebra-preserving operations on the ##F_k##.
 
  • #3
andrewkirk said:
Then the set of all elements that are in ##k## or more of the ##A_j## is

##F_k\triangleq \bigcup_{S\in D^m_k} \bigcap_{j\in S} A_j##

Confirm this to yourself before proceeding.

Sorry for the late reply, but I just got really scared after seeing all these notations and symbols that I don't understand, and kind of crawled into a metaphorical corner. Anyway, is ##S## the ##\sigma##-algebra ##O##? And a quick Google search tells me that ##F_k## is equal by definition to the right-hand side of the equation? I'm sorry; I just don't think that I can confirm that ##F_k \in O## without knowing what's being said, here.
 
  • #4
The symbol ##\triangleq## means 'is defined to be'. Some people use := instead, or ##=_{def}##.

The expression means the union, for all possible selections of k distinct integers in {1,...,m}, of the intersection of the k sets in ##A_1,...,A_m## that have those integers as index numbers.

##S## is the set containing the k chosen integers. It is not the sigma algebra.

In other words:
  1. choose k of the sets ##A_1,...,A_m## and take their intersection.
  2. Then take a different selection of k of those sets, take their intersection, then combine that (take the union) with the set from the previous step.
  3. Repeat that last step until all possible selections of k sets have been done.
 
  • #5
andrewkirk said:
In other words:
  1. choose k of the sets ##A_1,...,A_m##
  • ##A_1##,...,##A_m## and take their intersection.
  • Then take a different selection of k of those sets, take their intersection, then combine that (take the union) with the set from the previous step.
  • Repeat that last step until all possible selections of k sets have been done.

Okay, so the event space is closed under finite intersections and unions, so ##F_k\in O##. And following in suit of the case where ##m=2## and ##k=1##...

##B_k=\bigcup_{i=1}^{m} A_i \cap (\bigcup_{S\in D^m_k} \bigcap_{j\in S} A_j)^c##

I think...
 
  • #6
My professor went over the problem in class, and this is something else I came up with:

"Let ##I=\{1,...,m\}##. Define ##S=\{\sigma \in \mathbf{P}(I):|\sigma|=k\}##, where ##\mathbf{P}(I)## is the power set of ##I##. Then denote the k-element sets of integers from 1 to m as ##\sigma_n##, where ##n\in ℕ## and ##1\leq n\leq |S|##. Then define ##B_k=\bigcup_{n=1}^{|S|} [(\bigcap_{i\in \sigma_n} A_i)\cap(\bigcap_{j\neq i} A_j^c)]##, which is in ##B_k## since the event space is closed under finite set operations."
 

1. What is an event space?

An event space is a set of all possible outcomes of an experiment. It is denoted by the letter O and is used in probability theory to represent the sample space.

2. How is an event space related to probability?

An event space is important in probability as it helps us determine the likelihood of an event occurring. By listing all possible outcomes in the event space, we can calculate the probability of a specific event happening.

3. What is a finite number of events?

A finite number of events refers to a limited or countable number of possible outcomes in an event space. This means that there are a finite number of events that can occur in a given experiment.

4. How do you show that an event space is finite?

To show that an event space is finite, we need to list all possible outcomes or events in the sample space. If there are a limited and countable number of events, then the event space is considered finite.

5. Why is it important to show that an event space is finite?

Showing that an event space is finite is important because it allows us to apply the rules and formulas of probability to calculate the likelihood of specific events occurring. It also helps us understand the possible outcomes of an experiment and make informed decisions based on the probabilities.

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