Finding the Density Function for a Randomly Divided Rod

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Homework Help Overview

The discussion revolves around a probability theory problem involving a rod that is randomly divided into two parts. Participants are tasked with finding the density function of a random variable X, which represents the ratio of the longer part of the rod to the shorter part. The original poster expresses uncertainty about the existence of this density function.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the relationship between the lengths of the divided rod parts and the random variable X. There are discussions about the implications of dividing by zero and the uniform distribution of the shorter length. Some participants suggest using the cumulative distribution function (CDF) to derive the probability density function (pdf).

Discussion Status

Participants are actively engaging with the problem, with some providing hints and alternative approaches. There is acknowledgment of the complexity of the task, and while some express doubt about the existence of the density function, others argue for its validity based on the properties of continuous distributions.

Contextual Notes

There is a focus on the implications of dividing by zero and the nature of continuous distributions, with participants noting that endpoints of the interval have zero probability. The discussion also touches on the potential for X to be unbounded above.

trenekas
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Hello. I have problem with one task of probability theory. Hope that someone will be able to help me!

The task:

The rod is dividing in two parts accidentally. (Division is evenly distributed, don't know if its good saying in english). Find the density function of random variable X which is equal to longer part of rod divided by smaller part of rod.

So X can get infinity values i think. The smaller is 1, when rod is divided 0.5/0.5=1. And coming up to infinity when smaller part of rod coming up to 0. for example 0.99/0.01=99... and so on.

I don't know but i think that density function of this X does not exist. Or I am wrong?
 
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If the shorter length is y, the longer length is 1- y so the function is X= y/(1- y). Further, you seem to be saying that "y" is equally likely to be any number between 0 and 1/2.
 
It's often clearer conceptually to deal with the CDF and deduce the pdf later. HoI has given you the formula for X, so you want F(x) = P[X < x] = P[Y/(1-Y) < x]. Can you proceed from there?
 
HallsofIvy said:
If the shorter length is y, the longer length is 1- y so the function is X= y/(1- y). Further, you seem to be saying that "y" is equally likely to be any number between 0 and 1/2.
I think the task ask to do not the same as you say. I think we need 1-y/y... where 1-y is equal to longer part and y shorter...If i need dividing shorter from longer it much easier. or i don't understand you?
Maybe my opinion that this function does not exist is true?
 
trenekas said:
Hello. I have problem with one task of probability theory. Hope that someone will be able to help me!

The task:

The rod is dividing in two parts accidentally. (Division is evenly distributed, don't know if its good saying in english). Find the density function of random variable X which is equal to longer part of rod divided by smaller part of rod.

So X can get infinity values i think. The smaller is 1, when rod is divided 0.5/0.5=1. And coming up to infinity when smaller part of rod coming up to 0. for example 0.99/0.01=99... and so on.

I don't know but i think that density function of this X does not exist. Or I am wrong?

The parts (u,1-u) have zero probability for u = 0 or u = 1 because the endpoints of the interval [0,1] have zero probability for a continuous distribution. Therefore, we are (with probability 1) never dividing by zero, so a value X = ∞ has probability 0. We can even change to the open interval u ε (0,1), and so division by zero never happens---not even with probability zero. So, X does have a well-defined density function. Having X unbounded above is not a problem---lots of random variables are unbounded above, below, or both, and we deal with them with no problem. Of course, there is the issue of whether or not X has finite mean and/or variance, etc, but that is a separate question from the existence of a density for X.
 
Last edited:
ok understand.
 
But can't invent what this function shuold be. Maybe some hints? I thought more than an hour and have no idea.
 
Did you understand what I suggested? Let Y be the r.v. representing the distance from the nearer end. Y is uniformly distributed on [0, 0.5]. The CDF of X is F(x) = P[X < x] = P[(1-Y)/Y < x]. Can you evaluate that?
 
thank you haruspex. your hint was very helpfull. :smile:
 

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