Probability Distribution Function

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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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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?