Sigma Algebra on Omega (Sample Space)

In summary, the conversation discusses the definition of sigma algebras and their intersection. The example of coin toss outcomes is used to demonstrate how the sigma algebras change when given additional information. The speaker's question is about the intersection of two sigma algebras and whether specific sets are included in the intersection. The summary concludes that for the speaker's hypothesis to be true, all sets must be either empty or the entire state space.
  • #1
woundedtiger4
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Respected Members,

Suppose Ω is the set of eight possible outcomes of three coin tosses i.e. Ω={{HHH, HHT, HTH, HTTT, THH, THT, TTH, TTT}
So if we are not told the results then the sigma algebra ( denoted by F_α) at position α=0 is
F_0 = {∅, Ω}

Now if are told the first coin toss only then,
A_H={HHH, HHT, HTH, HTTT}, and A_T={THH, THT, TTH, TTT}
which the sigma Algebra at α=1 is
F_1={∅, Ω, A_H, A_T}

now in the attached picture the proof says that

A_1, A_2,..., A_n,... ε ∩_αεI F

if we just consider two sigma algebras for our convenience to check this let's take the intersection of two above coin toss's sigma algebras i.e. F_0 and F_1

for I= 0 and 1,

∩_αεI F_α = F_0 ∩ F_1 = {∅, Ω} ∩ {∅, Ω, A_H, A_T} = {∅, Ω} ----(BETA)

the proof says that A_1, A_2,..., A_n,... ε ∩_αεI F_α , and if we consider A_1 as A_H and A_2 as A_T then why are they not in the intersection of F_0 ∩ F_1 as shown in (BETA) ?

Thanks in advance.
 
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  • #2
You have [itex]\mathcal F_0=\{\emptyset,\Omega\}[/itex] and [itex]\mathcal F_1=\{\emptyset,A_H,A_T\Omega\}[/itex]. In particular, since [itex]\mathcal F_0\subseteq \mathcal F_1[/itex], your example has [itex]\mathcal F_0\cap\mathcal F_1=\mathcal F_0[/itex].

What you need for your hypothesis is [itex]A_i \in \mathcal F_0\cap\mathcal F_1=\mathcal F_0=\{\emptyset,\Omega\}[/itex] for every [itex]i[/itex]. That is, every [itex]A_i[/itex] is either empty or the whole state space; in particular, you can't use [itex]A_i=A_H[/itex] or [itex]A_i=A_T[/itex]. To verify the union, notice that the union is just [itex]\Omega[/itex] if at least one of your [itex]A_i=\Omega[/itex] and [itex]\emptyset[/itex] if (the only other possibility) every [itex]A_i=\emptyset[/itex]. In particular, either way, [itex]\bigcup_i A_i \in \mathcal F_0.[/itex]
 
  • #3
Why not A_i=A_H or A_T ? Let's say, A_1={ø}, A_2={Omega}, A_3=A_H and A_4=A_T then A_1, A_2, A_3, A_4 belongs to intersection_alpha belongs to I F_alpha, here F_alpha is F_0
After all A_H and A_T are the subsets of Omega, and definition 7 says that algebra is a collection of subsets of Omega.

Ps. Sorry, I am on train and typing this message on mobile therefore I am unable to add accurate symbols :(
 

Related to Sigma Algebra on Omega (Sample Space)

1. What is a sigma algebra on omega?

A sigma algebra on omega, also known as a sigma-algebra or a sigma-field, is a collection of subsets of a sample space (omega) that satisfies certain properties. It is an essential concept in measure theory and probability theory, as it allows for the formal definition of probability measures on a sample space.

2. What are the properties of a sigma algebra?

A sigma algebra must satisfy three properties: closure under countable unions, closure under complements, and containing the empty set. This means that if A and B are subsets of omega in the sigma algebra, then their union and complement must also be in the sigma algebra, and the empty set must always be included in the sigma algebra.

3. How is a sigma algebra different from a sigma ring?

A sigma algebra is a type of sigma ring, but it has an additional property of closure under countable unions. This means that while both a sigma algebra and a sigma ring contain the empty set, are closed under complements, and are closed under finite unions, only a sigma algebra is closed under countable unions.

4. Why is a sigma algebra important in probability theory?

In probability theory, a sigma algebra allows for the formal definition of probability measures on a sample space. This means that we can assign probabilities to events in a systematic and consistent way, allowing for the calculation of probabilities of more complex events and theorems such as the law of total probability and Bayes' theorem.

5. How is a sigma algebra used in practical applications?

Sigma algebras are used in a variety of practical applications, such as in finance, economics, and data analysis. They allow for the mathematical modeling and analysis of random events and allow for the calculation of probabilities and expectations, which are essential in decision-making and risk management.

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