An Introduction to Mathematical Statistics and Its Applications (6th Edition)

Published by Pearson
ISBN 10: 0-13411-421-3
ISBN 13: 978-0-13411-421-7

Chapter 3 Random Variables - 3.5 Expected Values - Questions - Page 147: 26

Answer

See explanation

Work Step by Step

Let $p_X(n),\ n= 0, 1, 2, 3, \ldots,$ be the pdf of $X$. $\begin{align*} E(X) &= \sum_{-\infty}^\infty n\cdot p_X(n) & [\ \text{Definition of}\ E(X)\ ] \\ &= \sum_{n=0}^\infty n\cdot p_X(n) & [\ \text{since}\ p_X(n) = 0, n \in \mathbb{Z}^-\ ] \\ &= \sum_{n=1}^\infty n\cdot p_X(n) & [\ \text{since}\ 0\cdot p_X(0) = 0\ ] \\ &= \sum_{n=1}^\infty \overbrace{\left(\sum_{k=1}^n 1\right)}^{=\; n} \cdot p_X(n) & \left[\ \text{since}\ \sum_{k=1}^n 1 = n\ \right] \\ &= \sum_{n=1}^\infty \sum_{k=1}^n p_X(n) \\ & \qquad\qquad [\ \text{for each fixed}\ n,\ n=1,2,3,\ldots, \\ & \qquad\qquad k\ \text{goes from}\ 1\ \text{to}\ n\ \text{(upwards; see diagram)}\ ] \\ &= \sum_{k=1}^\infty \sum_{n=k}^\infty p_X(n) \\ & \qquad\qquad \color{green}{[\ \text{switch order of summation}\colon}\ \\ & \qquad\qquad \color{green}{\text{for each fixed}\ k,\ n=1,2,3,\ldots,} \\ & \qquad\qquad \color{green}{n\ \text{goes from}\ k\ \text{to}\ \infty\ \text{(rightwards; see diagram)}\ ] }\\ E(X) &= \sum_{k=1}^\infty P(X\ge k) \\ \end{align*}$
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