Expected Value of Negative Binomial Random Variable

}\frac{(x-1+r-2)!}{(x-1)!(r-2)!}p^r(1-p)^{x-1}\\&=(r-1)\sum_{x=1}^{\infty}\frac{(x+r-3)!}{(x-1)!(r-2)!}p^r(1-p)^{x-1}\\&=(r-1)\sum_{x=1}^{\infty}\binom{x+r-3}{x-1}p^r(1-p)^{x-1}\\&=(r-1)p^r\sum_{x=1}^{\infty}\binom{x+r-
  • #1
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Given $X$ as a negative binomial random variable with parameters $r$ and $p$.
Find $E(\frac{r-1}{X-1})$.

As $E(g(X))$ is defined as $\sum_{x\in X(\Omega)}g(x)p(x)$,

this is my attempt in which I am stuck.
View attachment 2115

What can I do next? In the case $y=r-1$, is the sum invalid?

Thanks in advance!
 

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  • #2
\begin{align*}
E\left(\frac{r-1}{X-1}\right)&=\sum_{x=0}^{\infty}\frac{r-1}{x-1} \binom{x-1+r-1}{x-1}p^r(1-p)^{x-1}\\
&=\sum_{x=0}^{\infty}\frac{r-1}{x-1} \binom{x+r-2}{x-1}p^r(1-p)^{x-1}\\
&=\sum_{x=1}^{\infty}\frac{r-1}{x-1} \binom{x+r-2}{x-1}p^r(1-p)^{x-1}\\
&=(r-1)\sum_{x=1}^{\infty}\binom{x+r-2}{x-1}p^r(1-p)^{x-1}\\
&=(r-1)\sum_{x=1}^{\infty}\frac{(x+r-2)!}{(x-1)!(r-2)!}p^r(1-p)^{x-1}\\
&=(r-1)\sum_{x=1}^{\infty
 

FAQ: Expected Value of Negative Binomial Random Variable

What is the expected value of a negative binomial random variable?

The expected value of a negative binomial random variable is the average number of trials needed to reach a certain number of successes, given a probability of success for each trial. It is calculated by multiplying the number of trials by the probability of success for each trial.

How is the expected value of a negative binomial random variable different from the expected value of a binomial random variable?

The expected value of a negative binomial random variable measures the average number of trials needed to achieve a certain number of successes, while the expected value of a binomial random variable measures the average number of successes in a fixed number of trials. In other words, the negative binomial random variable allows for an indefinite number of trials, while the binomial random variable has a fixed number of trials.

How can the expected value of a negative binomial random variable be used in real-world situations?

The expected value of a negative binomial random variable can be used to predict the number of trials needed to achieve a certain number of successes in situations where the probability of success is known. This can be useful in fields such as economics, finance, and medicine.

Is the expected value of a negative binomial random variable always a whole number?

No, the expected value of a negative binomial random variable can be a decimal or a fraction, depending on the specific values of the number of trials and probability of success. However, if the number of trials and probability of success are both whole numbers, the expected value will also be a whole number.

How is the expected value of a negative binomial random variable calculated?

The expected value of a negative binomial random variable is calculated by multiplying the number of trials by the probability of success for each trial. This can be represented mathematically as E(X) = (r/p), where r is the number of successes and p is the probability of success for each trial.

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