Order statistics in the uniform (probability) distribution

In summary, the problem involves calculating the distribution function and probability density function of the sample median Y(n+1) for a random sample of i.i.d. variables from the U (0, 1) distribution. The solution involves arranging the values in increasing order and using a combination formula to calculate the probability of Y(n+1) falling within a given interval. However, there may be a discrepancy with the function used to calculate this probability. Any help with this issue would be greatly appreciated.
  • #1
Mathmos6
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Homework Statement


Hi there: I just need someone to tell me if I've made a mistake somewhere in my solution to this:

Suppose that X1 , . . . , X2n+1 are i.i.d. random variables that form a random sample
from the U (0, 1) distribution. Suppose that the values are arranged in increasing order as
Y1 ≤ Y2 ≤ . . . ≤ Y(2n+1) . Calculate expressions for the distribution function and for the probability density function of the random variable Y(n+1) (the sample median).

The Attempt at a Solution


Now if we want Y(n+1) to be in the interval [a,b] we need to have exactly n of the Xi in [0,a] and n+1 in [a,1], but ensure not all of the latter n+1 are in [b,1]. So we have [itex]{{2n+1}\choose{n+1}}a^n[(1-a)^n-(1-b)^n][/itex] where the [itex](1-a)^n-(1-b)^n[/itex] ensures not all n+1 of the latter Yi are in the [b,1] interval. But shouldn't there be some sort of symmetry in a and b with this function: shouldn't it be F(b)-F(a) where F'(x) is the pdf of the question? Because it doesn't look much like an F(b)-F(a) to me...

Thanks a lot,

Mathmos6
 
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  • #2
Anyone? Any help would be very much appreciated, no matter how small!
 

1. What is the uniform distribution?

The uniform distribution is a probability distribution where all outcomes are equally likely to occur. It is often represented by a rectangle on a graph, with a constant height and a base that represents the range of possible outcomes.

2. How are order statistics defined in the uniform distribution?

In the uniform distribution, order statistics refer to the arrangement of a set of random variables in increasing order. This means that the first order statistic is the smallest value, the second order statistic is the second smallest value, and so on.

3. What is the formula for calculating order statistics in the uniform distribution?

The formula for calculating the k-th order statistic in the uniform distribution is: X(k) = a + k(b-a)/n, where X(k) is the k-th order statistic, a and b are the minimum and maximum values in the distribution, and n is the sample size.

4. How do order statistics help in understanding the uniform distribution?

Order statistics provide information about the spread and central tendency of a set of random variables in the uniform distribution. They can also be used to estimate the parameters of the distribution, such as the minimum and maximum values.

5. Can order statistics be used to calculate probabilities in the uniform distribution?

Yes, order statistics can be used to calculate probabilities in the uniform distribution. For example, the probability that the second smallest value in a sample of size n is less than or equal to a given value x can be calculated using the formula P(X(2) ≤ x) = 2(x-a)/(b-a) - (x-a)^2/(b-a)^2, where a and b are the minimum and maximum values in the distribution.

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