Probability Questions for Uniform Random Variables on [0,1]

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Homework Help Overview

The discussion revolves around the probabilities associated with a sequence of uniform random variables defined on the interval [0,1]. Participants are exploring the probability that the supremum of the sequence equals 1 and the probability that two distinct variables in the sequence are equal.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants discuss the implications of the supremum being equal to 1 and consider the conditions under which this occurs. There is an exploration of the probability that all variables in the sequence are less than a certain value. Questions arise regarding the calculation of probabilities in the context of infinite sequences.

Discussion Status

Some participants have offered insights into the nature of the probabilities involved, while others express uncertainty about their reasoning. There is an ongoing examination of the assumptions related to the behavior of uniform random variables and the implications of having infinitely many samples.

Contextual Notes

Participants are grappling with the implications of infinite sequences and the properties of uniform distributions, particularly in relation to the supremum and equality of random variables. There is a recognition of the challenges posed by the infinite nature of the sequence in calculating probabilities.

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Homework Statement
Let {Xi} be a sequence of uniform random variables on [0,1]. What is P(sup {Xi} = 1) and P(Xi = Xj), i ≠ j?

The attempt at a solution
If sup{Xi} = 1, then either Xi is 1 for some i or there is an increasing sequence of the Xi's that converges to 1. The probability of the former is 0. I don't know how to calculate the probability of the latter.

For the second probability, if things were finite I would condition on the value of Xj and compute the probability that way. But in this case, I have no idea what to do.
 
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Consider [itex]P(\sup\{x_i\} \neq 1)[/itex]. If the supremum is not 1, it must be less than one, say [itex]\sup\{x_i\} = \alpha < 1[/itex]. If this is the case, then none of the [itex]x_i[/itex] can be greater than [itex]\alpha[/itex]. What is the probability of that?

For the second question, note that [itex]x_i = x_j[/itex] if and only if [itex]x_i - x_j = 0[/itex].
 
jbunniii said:
Consider [itex]P(\sup\{x_i\} \neq 1)[/itex]. If the supremum is not 1, it must be less than one, say [itex]\sup\{x_i\} = \alpha < 1[/itex]. If this is the case, then none of the [itex]x_i[/itex] can be greater than [itex]\alpha[/itex]. What is the probability of that?
Good tip. For a particular i, [itex]P(X_i > \alpha) = 1 - P(X_i \le \alpha) = 1 - \alpha[/itex], so the probability that [itex]X_i < \alpha[/itex] for all i must be [itex]\prod_i (1 - \alpha) = 0[/itex]. Hmm...this can't be right.

For the second question, note that [itex]x_i = x_j[/itex] if and only if [itex]x_i - x_j = 0[/itex].
Right. I don't know why this didn't occur to me. Thanks.
 
e(ho0n3 said:
Good tip. For a particular i, [itex]P(X_i > \alpha) = 1 - P(X_i \le \alpha) = 1 - \alpha[/itex], so the probability that [itex]X_i < \alpha[/itex] for all i must be [itex]\prod_i (1 - \alpha) = 0[/itex]. Hmm...this can't be right.

That's what I get. This shows that [itex]P(\sup\{x_i\} \leq \alpha) = 0[/itex] for all [itex]\alpha < 1[/itex]. So [itex]P(\sup\{x_i\} = 1)[/itex] must be 1.

It makes sense that this must be the case. If I choose infinitely many uniform numbers in [0,1], why should ALL of these numbers avoid some interval [itex][\alpha,1][/itex] with nonzero probability? What's special about the rightmost edge of the interval? Nothing at all.
 
Last edited:
You're right. My intuition about such things is, as you can tell, not very good. Thanks.
 

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