Order Statistics Probabilities

Click For Summary

Homework Help Overview

The discussion revolves around order statistics, specifically focusing on the distribution of the smallest value, X(1), from a set of independent and identically distributed random variables Xi, which follow the probability density function f(x) = (2x)I[0,1](x). Participants are tasked with finding the distribution of X(1) and determining the probability that the smallest value exceeds 0.2.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the cumulative distribution function FX(1)(x) and its derivation, questioning the validity of certain probability expressions. There is a focus on the relationship between the events of the random variables being less than or greater than a specific value.

Discussion Status

The discussion is active, with participants providing mathematical expressions and questioning the assumptions made in the derivation of probabilities. Some guidance has been offered regarding the correct interpretation of complementary events in probability.

Contextual Notes

Participants are reminded to show their attempts at solving the problem before receiving assistance, indicating a structured approach to the homework help process.

mathmajor23
Messages
29
Reaction score
0

Homework Statement


Let Xi ~ iid f(x) = (2x)I[0,1](x), i = 1,...,n.

Find the distribution of X(1). What is the probability that the smallest one exceeds .2?
 
Physics news on Phys.org
mathmajor23 said:

Homework Statement


Let Xi ~ iid f(x) = (2x)I[0,1](x), i = 1,...,n.

Find the distribution of X(1). What is the probability that the smallest one exceeds .2?

What work have you done on this so far? You need to show an attempt to solve this yourself before we can help.

RGV
 
FX(1)(x) = P(X(1) <= x)
= P(X1,...,Xn <= X)
=1-P(X1,...,Xn > X)
=1-P(X1>X)^n since the xi's are iid.
=1-[1-P(X1 <= X)]^n
=1-[1-F(x)]^n
=1-[1-∫ from 0 to x (2tdt)]^n
=1-(1-X^2)^n

For the probability, P(X1>.2) = 1-Fx(1) (0.2) = (1-(0.2)^2)^n = (0.96)^n
 
mathmajor23 said:
FX(1)(x) = P(X(1) <= x)
= P(X1,...,Xn <= X)
=1-P(X1,...,Xn > X)
=1-P(X1>X)^n since the xi's are iid.
=1-[1-P(X1 <= X)]^n
=1-[1-F(x)]^n
=1-[1-∫ from 0 to x (2tdt)]^n
=1-(1-X^2)^n

For the probability, P(X1>.2) = 1-Fx(1) (0.2) = (1-(0.2)^2)^n = (0.96)^n

I hope you were just being sloppy and don't really believe that
[tex]P(X_1, X_2, \ldots, X_n \leq x) = 1 - P(X_1, X_2, \ldots, X_n > x) \, \leftarrow \text{FALSE!}[/tex] because that is not valid. For two events A and B we have P(A) = 1 - P(B) if the events A and B are complementary (that is, have no points in common and together cover the entire sample sample space). Do the events [itex]\{X_1, \ldots,X_n \leq x \}[/itex] and [itex]\{X_1,\dots,X_n > x\}[/itex] look complementary to you? (Try drawing these for n = 2.) Of course, what is true is that [itex]P(X_i > x) = 1-P(X_i \leq x)[/itex] for each [itex]X_i[/itex] separately. You need to decide whether or not we have
[tex]P(X_1,\ldots,X_n > x) = (1-x^2)^n \text{ or } P(X_1,\ldots,X_n > x) = 1-(1-x^2)^n \,.[/tex]

RGV
 
Last edited:

Similar threads

Replies
8
Views
1K
  • · Replies 5 ·
Replies
5
Views
2K
Replies
2
Views
1K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
1
Views
1K
Replies
3
Views
2K
Replies
1
Views
2K
  • · Replies 5 ·
Replies
5
Views
1K
  • · Replies 2 ·
Replies
2
Views
1K