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Follow these steps:

- Find all the values that the random variable (RV) can take, x.
- For each x, find the probability that the RV takes than value, p(x).
- Multiply them: x*p(x).
- Sum these over all possible values of x.

The above sum is the expected value of the RV, X.

Q: How do you compute expected value from random discreet variable?

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You need to determine the area under the curve between the values in question. This is easy to do because there are tables that give the area values.

Almost all statistical distribution have a mean. It is the expected value of the random variable which is distributed according to that function.

If x = 1 then X is not really a random variable but a constant.

A random variate is a particular outcome of a random variable: the random variates which are other outcomes of the same random variable would have different values.

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Expected value of a random variable requires that the random variable can be repeated in experiment indefinitely. If the random variable can only be repeated finite times, e.g. once, there is an inadequacy of the expected value principle for a decision maker.

30.47

No. The mean is the expected value of the random variable but you can also have expected values of functions of the random variable. If you define X as the random variable representing the result of a single throw of a fair die, the expected value of X is 3.5, the mean of the probability distribution of X. However, you play a game where you pay someone a certain amount of money for each throw of the die and the other person pays you your "winnings" which depend on the outcome of the throw. The variable, "your winnings", will also have an expected value. As will your opponent's winnings.

It is a discrete random variable.

When it is random it is variable.

This is supposed to be Y > u

The expected value is the long-run average value of repetitions of the experiment it represents.

You need to determine the area under the curve between the values in question. This is easy to do because there are tables that give the area values.

we compute it by using their differences

Almost all statistical distribution have a mean. It is the expected value of the random variable which is distributed according to that function.

If x = 1 then X is not really a random variable but a constant.