Measure theory and independent sets

In summary, the conversation discusses the concept of a smallest subfield of a given field, and how it relates to independent sets and probability measures. The specific problem involves sets A1 through Ak being independent and belonging to a sigma-field \mathcal{F}. The task is to find the smallest subfield \mathcal{F}_k that contains A1 through Ak. The smallest subfield is not simply a set containing A1 through Ak, but rather a special kind of collection called a sigma-field. Further understanding of the terms \sigma-field and subfield is necessary to solve the problem.
  • #1
aresnick
11
0

Homework Statement


Let [tex]\mathscr{X}[/tex] be a set, [tex]\mathscr{F}[/tex] a [tex]\sigma-[/tex]field of subsets of S, and [tex]\mu[/tex] a probability measure on [tex]\mathscr{F}[/tex]. Suppose that [tex]A_{1},\ldots,A_{n} [/tex] are independent sets belonging to [tex]\mathscr{F}[/tex]. Let [tex]\mathscr{F}_{k}[/tex] be the smallest subfield of [tex]\mathscr{F}[/tex] containing [tex]A_{1}, \ldots, A_{k}[/tex]. Show that if [tex]A \in \mathscr{F}_{k}[/tex], then [tex]A, A_{k+1}, \ldots, A_{n}[/tex] are indepdendent.

Homework Equations


Two sets are independent iff [tex]\mu(A \cap B) = \mu(A)\mu(B)[/tex].

The Attempt at a Solution


Really, my question here is what the smallest field is. It seems that, given a set [tex]\mathscr{X}[/tex], the smallest field [tex]\mathscr{F}_{s}[/tex] containing it is simply [tex]\left\{\emptyset, \{ \mathscr{X}\}\right\}[/tex]. Am I just crazy?
 
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  • #2
It asks you to find the smallest subfield containing A1, ..., Ak. If someone asks you for the smallest natural greater than 10, the answer is 11, even if 0 is the smallest natural.
 
  • #3
AKG said:
It asks you to find the smallest subfield containing A1, ..., Ak. If someone asks you for the smallest natural greater than 10, the answer is 11, even if 0 is the smallest natural.

But I'm suggesting that the smallest set that contains [tex]A_{1} \ldots A_{k} [/tex] is simply a set containing [tex]\left\{A_{1} \ldots A_{k}\right\}[/tex] and the empty set (since every set must contain the empty set). It just seemed like a very simple object, in that case.

Does that make sense?
 
  • #4
aresnick said:
But I'm suggesting that the smallest set that contains [tex]A_{1} \ldots A_{k} [/tex] is simply a set containing [tex]\left\{A_{1} \ldots A_{k}\right\}[/tex] and the empty set (since every set must contain the empty set). It just seemed like a very simple object, in that case.

Does that make sense?
No.

First of all, do you recognize the difference between

[tex]A_1 \in \{ A_1, \dots , A_k\}[/tex]

and

[tex]A_1 \subset \{ A_1 ,\dots ,A_k \}[/tex]

The first line is always true, the second is usually not. {A1, ..., Ak} is a set, but it's elements aren't just any elements, they are sets too! It is a set of sets. Normally, to avoid confusion, we like to say "collection of sets" instead of "set of sets," but they mean the same thing. The things Ai are also sets, but their elements will be elements of X. So Ai is a subset of X, {A1, ..., Ak} is a collection/set of subsets of X, i.e. {A1, ..., Ak} is an element of the power set of X.

Another point of confusion might be the word "contain." Does "x contains y" mean [itex]y \in x[/itex] or [itex]y \subset x[/itex]. It could mean either, depending on the context. So note the following:

[tex]A_1 \in \{ A_1 ,\dots , A_k\}[/tex]
An element of a collection of sets is a set.

[tex]A_1 \not\subset \{ A_1 ,\dots , A_k\}[/tex]
(except in some weird situations that don't concern us here)

[tex]\{ A_1, A_2 \} \subset \{ A_1 ,\dots , A_k\}[/tex]
[tex]\{ A_1\} \subset \{ A_1 ,\dots , A_k\}[/tex]
A subset of a collection of sets is itself a collection of sets.

[tex]\{ A_1 \} \notin \{ A_1 ,\dots , A_k\}[/tex]
(except in weird situations)

So the question gives you a set X. To make things very clear, we will use lower case roman letters when denoting elements of X, like x. We will use upper case roman letters when denoting subsets of X, like Y. We will use capital script letters when denoting collections of subsets of X, like [itex]\mathcal{F}[/itex]. So we have:

[tex](X, \mathcal{F} , \mu )[/tex]

our probability space. It then says that for i = 1, ..., n:

[tex]A_i \in \mathcal{F}[/tex]

with the Ai being independent. You want to consider the subfield (not just any old subcollection) [itex]\mathcal{F}_k \subset \mathcal{F}[/itex] such that for all i = 1, ..., k:

[tex]A_i \in \mathcal{F}_k[/tex]

with [itex]\mathcal{F}_k[/itex] as small as possible. Note that [itex]\mathcal{F} \subset \mathcal{F}[/itex] and for all i = 1, ..., k:

[tex]A_i \in \mathcal{F}[/tex]

but [itex]\mathcal{F}[/itex] is generally not the smallest.

So what is the smallest subfield of [itex]\mathcal{F}[/itex] the contains A1 through Ak? It's probably not going to be {A1, ..., Ak} because although that is a collection of sets, it is probably not an [itex]\sigma[/itex]-field. An [itex]\sigma[/itex]-field is a special kind of collection.

[tex]\{ \emptyset , A_1 ,\dots , A_k \}[/tex]

is probably not a subfield either. In order to figure out what [itex]\mathcal{F}_k[/itex] should be, you need to first make sure you understand the meaning of [itex]\sigma[/itex]-field and subfield. Come back when you know those definitions and you've absorbed the above.
 

FAQ: Measure theory and independent sets

1. What is Measure Theory?

Measure theory is a branch of mathematics that deals with the concept of "measure", which is essentially a way to assign a numerical value to a set or collection of objects. It provides a framework for understanding and quantifying the size, or "measure", of different sets.

2. What is an independent set?

In measure theory, an independent set is a collection of measurable sets that do not overlap in any significant way. This means that the "measure" of their combined area is equal to the sum of their individual measures. In other words, the independent sets do not share any common elements.

3. How is independence of sets determined?

The independence of sets is determined using the concept of "mutual exclusivity". This means that the sets do not share any common elements, and therefore, their measures are additive. In other words, the measure of their intersection is equal to 0.

4. What is the importance of independent sets in measure theory?

Independent sets are important in measure theory because they allow for the accurate and precise quantification of the size or measure of different sets. They also help in understanding the relationship between different sets and their measures, which is crucial in many mathematical and scientific applications.

5. How are independent sets used in real-world applications?

Independent sets have many real-world applications, particularly in statistics and probability. For example, in probability theory, independent sets are used to calculate the probability of multiple events occurring simultaneously. In statistics, they are used to determine the relationship between different variables and their measures, which is important in analyzing data and making predictions.

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