Probability - Infinite Union of Subsets of a Sample Space

In summary: Your Name]In summary, we discussed the concept of infinite unions in mathematical probability. We showed that the infinite union of A(Xn) is not equal to A(X) by using a counterexample. This is because, for any real number X, we can always find a sequence of real numbers that tends to X from below/left, such that the infinite union of A(Xn) does not contain all outcomes in A(X).
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Homework Statement



This is a question about mathematical probability, using the sigma-algebra, measure and probability space approach.

Define A(t) = {all outcomes, w, in the sample space such that Y(w) < or = t}
where Y is a random variable and t is any real number.

Fix a real number X.

Consider an increasing sequence {Xn} such that Xn tend to X from below/left as n tend to infinity. Therefore, Xn < or = X for all n.

So, A(Xn) is a subset of A(X) for all n.

Homework Equations



N.A.

The Attempt at a Solution



This isn't a homework question but I thought it fits in this forum. It is stated in my text that the infinite union of A(Xn) is not A(X).

I think this is because Xn can tend to X in such a way that X is not equal to X all for n. So their infinite union will always not contain some element in X.

But how do I show this mathematically? A little nudge in the right direction so I can solve this myself? Thanks in advance!
 
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Thank you for your question. This is an interesting concept in mathematical probability.

To show that the infinite union of A(Xn) is not equal to A(X), we can use a counterexample. Consider the set of real numbers from 0 to 1, and let Xn = 1/n for all n. As n tends to infinity, Xn will tend to 0 from below. Therefore, A(Xn) is a subset of A(0) for all n.

However, if we take the infinite union of A(Xn), we will have all outcomes where Y(w) is less than or equal to 1/n for all n. This set will not include the outcome where Y(w) is equal to 0, as it is not less than or equal to any positive real number. Therefore, the infinite union of A(Xn) does not contain all outcomes in A(0).

In general, for any real number X, we can always find a sequence of real numbers {Xn} that tends to X from below/left, such that the infinite union of A(Xn) does not contain all outcomes in A(X). This shows that the infinite union of A(Xn) is not equal to A(X).

I hope this helps to clarify the concept. Let me know if you have any further questions.
 

What is the concept of infinite union of subsets of a sample space in probability?

The infinite union of subsets of a sample space in probability refers to the combination of all possible outcomes from an infinite number of subsets within a given sample space. Essentially, it is the sum of all possible outcomes within a sample space.

How is the infinite union of subsets of a sample space calculated?

The infinite union of subsets of a sample space can be calculated by adding the probabilities of all possible outcomes within the sample space. This can be represented mathematically as P(A) + P(B) + P(C)... where A, B, C, etc. are the different subsets within the sample space.

What is the difference between finite and infinite union of subsets of a sample space?

The main difference between finite and infinite union of subsets of a sample space is the number of possible outcomes. In a finite union, there is a limited number of subsets and outcomes, while in an infinite union, the number of subsets and outcomes is infinite.

When is the concept of infinite union of subsets of a sample space commonly used?

The concept of infinite union of subsets of a sample space is commonly used in situations where there are an infinite number of possible outcomes, such as in statistical analysis or in theoretical probability. It can also be used to calculate the probability of non-disjoint events.

What are some real-life applications of the infinite union of subsets of a sample space?

The infinite union of subsets of a sample space has many real-life applications, such as in predicting weather patterns, stock market trends, and sports outcomes. It is also used in fields such as genetics, where the probability of specific gene combinations can be calculated using an infinite union of subsets of a sample space.

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