Expected value and equality to sums

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Discussion Overview

The discussion revolves around the expected value of a non-negative integer-valued random variable 'N' and its representation as sums of probabilities. Participants explore the mathematical expressions related to the expected value and seek clarification on how to express certain concepts using indicator random variables.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • Some participants inquire about demonstrating the equality $E[N]=\sum_{k=1}^\infty P{\{N\geq k\}}=\sum_{k=0}^\infty P{\{N>k\}}$.
  • One participant mentions defining a sequence of indicator random variables $I_n$ and expresses uncertainty about how to relate 'X' to $I_n$.
  • Another participant reflects on understanding the equation by relating it to the expectation of a random variable derived from a fair dice toss.
  • Several identities involving binomial coefficients and indicator variables are proposed as potentially useful in the discussion.

Areas of Agreement / Disagreement

The discussion does not appear to reach a consensus, as participants express different levels of understanding and uncertainty regarding the mathematical expressions and their implications.

Contextual Notes

Participants have not fully resolved the mathematical steps involved in expressing the expected value and its relationship to indicator random variables. There are also varying interpretations of the identities presented.

Who May Find This Useful

Readers interested in probability theory, particularly those studying expected values and indicator random variables, may find this discussion relevant.

WMDhamnekar
MHB
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How to show that$E[N]=\displaystyle\sum_{k=1}^\infty P{\{N\geq k\}}=\displaystyle\sum_{k=0}^\infty P{\{N>k\}}$

If any member here knows the answer, may reply to this question.:confused:
 
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Dhamnekar Winod said:
How to show that$E[N]=\displaystyle\sum_{k=1}^\infty P{\{N\geq k\}}=\displaystyle\sum_{k=0}^\infty P{\{N>k\}}$

If any member here knows the answer, may reply to this question.:confused:
Hello,
'N' denote a non-negative integervalued random variable.
 
Dhamnekar Winod said:
Hello,
'N' denote a non-negative integervalued random variable.
Hello,

I got the answer after doing some carefully thinking.
 
Dhamnekar Winod said:
Hello,

I got the answer after doing some carefully thinking.

Perhaps yu'd like to share your solution so that others facing the same or similar question can benefit from your work?
 
Hello,
If we define the sequence of random variable $I_n$ (Indicator random variable), n > 1 by

$$I_n= \left \{ {1,\text{if n < X} \atop \text{0, if n>X}} \right.$$. Now express X in terms of $I_n.$ (Actually, I don't know how to express in terms of $I_n$:confused:)

I understood the equation in #1 by using the expectation of random variable X(outcome of a toss of a fair dice)is equal to summation of the probabilities of X > n, where range of n is 0 to $\infty$

I think the following below mentioned identities will be useful here.

$$ a)(1-1)^N= \left \{{\text{1, if N > 0}\atop \text{0, if n < 0}} \right.$$
$$b)(1-1)^N=\displaystyle\sum_{n=0}^n\binom{N}{i}*(-1)^i$$

$$ c)1-I=\displaystyle\sum_{n=0}^n\binom{N}{i}*(-1)^i$$

$$ d)I=\displaystyle\sum_{n=1}^n\binom{N}{i}*(-1)^i$$

If you want to show this equation in mathematical language, you may reply to that effect.:)
 
Last edited:

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