Respuesta :
Throwing a coin until it lands tails is an example of a discrete random variable which does not have a finite expectation.
For the given question,
A discrete random variable is a type of variable whose value depends upon the numerical outcomes of a certain random phenomenon. Discrete random variables are always whole numbers, which are easily countable.
It is a variable that can take on a finite number of distinct values and takes numerous values. It is also known as a stochastic variable. When you consider probabilistic experiments with infinite outcomes, it is easy to find random variables with an infinite expected value.
Let X be a random variable that is equal to 2ⁿ with probability 2⁻ⁿ (for positive integer n). Then,
[tex]E(X)=\sum_{n:1}^{\infty} |2^{-n}2^{n}|[/tex]
⇒ [tex]E(X)=\sum_{n:1}^{\infty} (1)[/tex]
⇒ [tex]E(X)=\infty[/tex]
Consider the following example,
You throw a coin until it lands tails.
Let n be the number of heads
Then number of heads can be found by, 2ⁿ
Now, the expected value function is
[tex]E(X)=\frac{1}{2}(2^{0} )+ \frac{1}{4}(2^{1} )+....[/tex]
⇒ [tex]E(X)=\sum_{n:1}^{\infty} |2^{-n}2^{n-1}|[/tex]
⇒ [tex]E(X)=\sum_{n:1}^{\infty} \frac{1}{2}[/tex]
⇒ [tex]E(X)=\infty[/tex]
Since the number of outcomes is infinite. The probability of each outcome decreases exponentially.
Hence we can conclude that throwing a coin until it lands tails is an example of a discrete random variable which does not have a finite expectation.
Learn more about discrete random variable here
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