If X ∼ Uniform(−1, 1) find the pdf of Y = |X|

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Discussion Overview

The discussion centers around finding the probability density function (pdf) of the random variable Y, defined as the absolute value of another random variable X, which follows a uniform distribution between -1 and 1. Participants explore the implications of the modulus operation on the distribution and the necessary steps to derive the cumulative distribution function (cdf) for Y.

Discussion Character

  • Homework-related
  • Mathematical reasoning
  • Conceptual clarification

Main Points Raised

  • One participant expresses confusion regarding the non-monotonic nature of the graph and the need to split the analysis for different ranges of Y.
  • Another participant suggests calculating the cdf ##F_Y(y)## for Y, emphasizing the need to determine the values of X that satisfy the condition for Y.
  • Some participants propose that Y appears to be uniform between 0 and 1, although this is not universally accepted.
  • There is mention of using the change-of-variable formula for random variables, but it is noted that this method is not applicable to the absolute value function without piecewise consideration.
  • A participant reiterates the need to find the probability that |X| ≤ y, indicating the importance of correctly identifying the ranges for X.
  • Clarifications are made regarding the notation and conventions used in probability expressions to avoid confusion.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the approach to take or the nature of the distribution of Y, with multiple competing views and methods being discussed.

Contextual Notes

Participants highlight the complexity introduced by the modulus function, which requires careful consideration of piecewise definitions and the ranges of X. There are unresolved questions regarding the correct application of probability concepts and notation.

Who May Find This Useful

This discussion may be useful for students or individuals studying probability theory, particularly those interested in transformations of random variables and the implications of absolute values in probability distributions.

BobblyHats97
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This question is killing me.

I know the graph is non-monotonic so i have to split up finding F(Y) for -1<Y and Y<1 but then what do I do with the modulus? >.<

Any help would be greatly appreciated! Thank you so much x
 
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You know the pdf of X, which is as simple as a pdf can be.
You have correctly assessed that the next step is to work out the cdf ##F_Y## of Y. THat is, for a given ##y\in[0,1]##, we need to work out what is ##F_Y(y)##?

##F_Y(y)## is the probability that ##Y\leq y##. What values of ##X## produce a value of ##Y## that satisfies that? Can you work out the probability that ##X## has such a value?
 
By inspection, Y is uniform between 0 and 1.
 
andrewkirk said:
Unfortunately that only works for increasing or decreasing functions, so it can't be applied to the absolute value function.
Why not apply it piecewise, from -1 to 0 then from 0 to 1?
 
andrewkirk said:
You know the pdf of X, which is as simple as a pdf can be.
You have correctly assessed that the next step is to work out the cdf ##F_Y## of Y. THat is, for a given ##y\in[0,1]##, we need to work out what is ##F_Y(y)##?

##F_Y(y)## is the probability that ##Y\leq y##. What values of ##X## produce a value of ##Y## that satisfies that? Can you work out the probability that ##X## has such a value?
I'm sorry, can you explain what you just said? I'm tired and feeling slightly brain dead but this homework is due in tomorrow :(

I've calculated that the pdf is 1/2 for -1<x<1 and 0 otherwise.

I understand that to find the probability that Y≤y i have to fine the probability that |x|≤y for -1<Y<0 and 0<Y<1 but how do I do that? Am I missing something obvious? Can I just get rid of the modulus because I'm considering all possible values on Y?
 
BobblyHats97 said:
I understand that to find the probability that Y≤y i have to fine the probability that |x|≤y for -1<Y<0 and 0<Y<1 but how do I do that?
You need to be more careful with upper and lower case, in order to avoid confusing yourself. The standard convention, which works nicely, is to use upper case for a random variable and lower case for a plain old number. So when we write ##Prob(Y\leq y)## we mean the probability that the random variable ##Y## is less than or equal to the number ##y##.
So don't write things like ##|x|≤y## as you did above, because you'll just confuse yourself. If you instead write ##|X|\leq y## then it's easy to see how to proceed. You are trying to find the probability that the random variable ##X## has an absolute value in the range ##[0,y]##. So ask yourself:
1. What range does ##X## have to be in for that to be the case?
2. What is the probability of ##X## being in that range?
 

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