Determining the PDF Given a DF

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In summary, the conversation is about determining the pdf given a DF. The function F(x) is defined for different ranges of x and the question is asked whether the pdf is the derivative of the df. The conclusion is that the pdf is a different function, which is f(x)= x for 0≤x<1 and f(x)= 1/2 for 1≤x<2, and it is not needed to calculate the probability of x between 0 and 1. The conversation also includes a correction to the function F(x) to be x^2/2 instead of x^2/x.
  • #1
brendan
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I have been asked to determine the pdf given a DF.

F(x) = 0 for x<0
F(x) = x^2/x for x 0<= x < 1
F(X) = x/2 for 1<=x<2
F(x) = 1 for x>= 2

Is the pdf the derivative of the df

So if you wanted the probability of x between 0 and 1
The pdf would just be x ?


regards
Brendan
 
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  • #2
brendan said:
I have been asked to determine the pdf given a DF.

F(x) = 0 for x<0
F(x) = x^2/x for x 0<= x < 1
Surely this isn't right? did you mean x^2/2, so that F is continuous at x=1?

F(X) = x/2 for 1<=x<2
F(x) = 1 for x>= 2

Is the pdf the derivative of the df

So if you wanted the probability of x between 0 and 1
The pdf would just be x ?


regards
Brendan
You don't need the pdf at all to answer that question. F(x) is the probability that the random variable is between 0 and x. The probablity that x is between 0 and 1 is just F(1)= 1/2.

The pdf is the function
f(x)= 0 for x< 0
f(x)= x for [itex]0\le x< 1[/itex]
f(x)= 1/2 for [itex]1\le x< 2[/itex]
f(x)= 0 for [itex]2\le x[/itex]
 
  • #3
Thanks alot. You are right it is x^2/2 my mistake.
So does that mean if x = 1/2 , F(1/2) = 1/2 ?
 

1. What is a PDF and how is it related to a DF?

A PDF, or probability density function, is a mathematical function that describes the probability distribution of a continuous random variable. It is related to a DF, or cumulative distribution function, as the derivative of the DF is the PDF.

2. How do you determine the PDF given a DF?

To determine the PDF given a DF, you can use the relationship between the two functions and take the derivative of the DF. This will give you the mathematical expression for the PDF.

3. What is the difference between a PDF and a PMF?

A PDF is used to describe the probability distribution of a continuous random variable, while a PMF (probability mass function) is used for discrete random variables. A PDF is a continuous function, while a PMF is a discrete function.

4. Can the PDF be negative?

Yes, the PDF can have negative values. This is because the PDF is a probability density, not a probability itself. The total area under the PDF must equal 1, but individual points on the PDF can have negative values.

5. How is the PDF used in statistics and data analysis?

The PDF is used in statistics and data analysis to describe the probability distribution of a continuous random variable. It is used in calculations of probabilities and to make predictions about future outcomes based on past data. It is also used to compare different data sets and identify patterns in the data.

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