MHB Expected value and equality to sums

Click For 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
MHB
Messages
376
Reaction score
28
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:
 
Mathematics news on Phys.org
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:
Thread 'Erroneously  finding discrepancy in transpose rule'
Obviously, there is something elementary I am missing here. To form the transpose of a matrix, one exchanges rows and columns, so the transpose of a scalar, considered as (or isomorphic to) a one-entry matrix, should stay the same, including if the scalar is a complex number. On the other hand, in the isomorphism between the complex plane and the real plane, a complex number a+bi corresponds to a matrix in the real plane; taking the transpose we get which then corresponds to a-bi...

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
15
Views
2K
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 14 ·
Replies
14
Views
2K