Finding PDF of Y from Uniform Distribution of X1-Xn

In summary, the probability density function of Y = min[X1, X2, ... , Xn] is n(1-y)^(n-1), where X1,...,Xn are independently and identically distributed from the uniform distribution on [0, 1]. This is found by first finding the CDF of Y and then differentiating it with respect to y.
  • #1
jetoso
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0
Suppose X1, . . . ,Xn are independently and identically from the uniform distribution on [0, 1]. Find the probability density function of Y = min[X1, X2, ... , Xn].
I do not know how to formulate this problem. I know that the pdf has to be some integral, but no clue so far.
 
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  • #2
First find the CDF of Y: G(y) = Prob(Y<y) = Prob(min{X1,...,Xn} < y) = Prob(at least one X is < y) = Prob(not all X are > y) = 1 - Prob(all X are > y) = 1 - [1 - F(y)]n = 1 - (1 - y)n. Now find the PDF by differentiating with respect to y.
 
  • #3
Thanks

That's true; since we have that X1,...,Xn are iid, and does not matter if we have <= or < because is a continuous function, then pdf = f(y) = F'(y) = -n(1-y)^(n-1)(-1) = n(1-y)^(n-1).

Thanks.
 

Related to Finding PDF of Y from Uniform Distribution of X1-Xn

1. What is a Uniform Distribution?

A Uniform Distribution is a type of probability distribution where all outcomes have an equal chance of occurring. This means that the probability of any given outcome is the same as the probability of any other outcome.

2. How is a Uniform Distribution represented mathematically?

A Uniform Distribution is represented by the formula f(x) = 1/(b-a), where a is the minimum value and b is the maximum value of the distribution. This formula is used to calculate the probability of a specific outcome occurring.

3. What is the relationship between X1-Xn and Y in this scenario?

In this scenario, X1-Xn represents a sample of n values from a Uniform Distribution. Y is a transformed variable that is created by finding the PDF (Probability Distribution Function) of X1-Xn. This means that Y is a function of X1-Xn and is used to determine the probability of a particular outcome.

4. How is the PDF of Y found from Uniform Distribution of X1-Xn?

The PDF of Y can be found using the following steps:

  1. Calculate the mean and standard deviation of X1-Xn.
  2. Transform X1-Xn to Z-scores by subtracting the mean and dividing by the standard deviation.
  3. Use the Z-scores to find the cumulative probability for each value of Y.
  4. Take the derivative of the cumulative probability to find the PDF of Y.

5. What is the significance of finding the PDF of Y from Uniform Distribution of X1-Xn?

Finding the PDF of Y allows us to understand the probability distribution of a transformed variable that is derived from a Uniform Distribution. This information can be used in a variety of scientific and statistical analyses, such as hypothesis testing, data modeling, and risk assessment.

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