MHB Expected value and equality to sums

AI Thread Summary
The discussion centers on demonstrating the equality of the expected value of a non-negative integer-valued random variable, expressed as E[N] = ∑ P{N ≥ k} = ∑ P{N > k}. Participants explore the use of indicator random variables to express this relationship, with one member suggesting that the expectation can be understood through the probabilities of outcomes exceeding a certain value. Additionally, various mathematical identities are mentioned that may aid in proving the equality. The conversation encourages sharing solutions to benefit others facing similar questions.
WMDhamnekar
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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.:)
 
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