How do you find the expected value of a discrete random variable?

For a discrete random variable, the expected value, usually denoted as or , is calculated using: μ = E ( X ) = ∑ x i f ( x i )

How do you find the discrete random variable of a PDF?

The discrete probability density function (PDF) of a discrete random variable X can be represented in a table, graph, or formula, and provides the probabilities Pr(X = x) for all possible values of x….Example: A Six-Sided Die.

Outcome	Probability
2	1/6
3	1/6
4	1/6
5	1/6

Which of the following denotes the expected value of a random variable?

The expected value of a random variable is denoted by E[X]. The expected value can be thought of as the “average” value attained by the random variable; in fact, the expected value of a random variable is also called its mean, in which case we use the notation µX. (µ is the Greek letter mu.) xP(X = x).

What is the expected value of a variable?

The expected value of a random variable is the weighted average of all possible values of the variable. The weight here means the probability of the random variable taking a specific value.

What is discrete random variable PDF?

A discrete probability distribution function has two characteristics: Each probability is between zero and one, inclusive. The sum of the probabilities is one.

Which of the following best describes the expected value of a discrete random variable?

Which of the following best describes the expected value of a discrete random variable? It is the geometric average of all possible outcomes.

What is expected value example?

Expected value is the probability multiplied by the value of each outcome. For example, a 50% chance of winning $100 is worth $50 to you (if you don’t mind the risk). We can use this framework to work out if you should play the lottery.