Probability Distribution Function

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Homework Help Overview

The discussion revolves around understanding a probability distribution function and its related concepts, including the probability density function, mean, and median. Participants are exploring the properties and requirements of cumulative distribution functions (CDF) and probability density functions (PDF).

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants are questioning the validity of the provided example as a probability density function or cumulative distribution function. There are discussions about the definitions and requirements for these functions, as well as the implications of negative probabilities.

Discussion Status

Some participants have offered clarifications regarding the definitions of CDF and PDF, while others are prompting the original poster to reconsider the assumptions made about the example. The discussion is ongoing with various interpretations being explored.

Contextual Notes

There are constraints related to the original example provided, which may not meet the criteria for a valid probability distribution function. Participants are encouraged to reflect on the properties of CDFs and PDFs to better understand the problem.

p.mather
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Homework Statement



Given the probability distribution function:

See attachment.

Determine the:

1. Probability density function.
2. The mean.
3. The median.

Homework Equations



Hello,

I am really struggling with this subject area, this is an example I have found, would someone be able to go through a solution so I can begin to understand it a bit more.

Appreciate any help.

Thanks.

The Attempt at a Solution

 

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It's pretty hard to work with that "example" since it is neither a probability density function nor a cumulative distribution function.

Question for you: How do I know that?
 
The probability density function is F'(x) , the derivative of F(x).
The mean is [tex]\int x F'(x) dx[/tex] taken over the interval where F'(x) is not zero.
The median is found by solving for x in the equation F(x) = 1/2

(The mode (or modes) is found by finding the value (or values) where F'(x) is maximum. )

I don't have time to go through this in detail now. If you have further questions, ask.
 
Stephen Tashi said:
The probability density function is F'(x) , the derivative of F(x).
The mean is [tex]\int x F'(x) dx[/tex] taken over the interval where F'(x) is not zero.
The median is found by solving for x in the equation F(x) = 1/2

(The mode (or modes) is found by finding the value (or values) where F'(x) is maximum. )

I don't have time to go through this in detail now. If you have further questions, ask.

As i was saying i am not good at this at all and its something i need to begin to understand. Would you please be able to provide a worked solution so i can begin to understand. It would be greatly appreciated. Thanks.
 
LCKurtz said:
It's pretty hard to work with that "example" since it is neither a probability density function nor a cumulative distribution function.

Question for you: How do I know that?

Do not mindlessly start taking derivatives of that function. First Re-read LCKurtz post.

What is the range of a CDF?, and what are the restriction for the range of a PDF?

What are the requirements for a function to be a CDF or a PDF?
 
The cumulative distribution (sometimes simply called "the distribution") of a random variable [itex]X[/itex] is the function [itex]F(x)[/itex] that gives the probability that [itex]X \leq x[/itex].

The example you gave:

[tex]F(x) = 1 - e^{2x}[/tex] for [tex]x \geq 0[/tex] doesn't make sense as a cumulative distribution because for positive values of [itex]x[/itex] , [itex]F(x) < 0[/itex] and probabilities must be non-negative numbers.

One way to fix the typo in the example is say that [itex]F(x)[/itex] is defined by:

[tex]F(x) = 1 - e^{-2x}[/tex] for [itex]x \geq 0[/itex][tex]F(x) = 0[/tex] for [itex]x < 0[/itex]

Is this much clear?
 

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