It's the expected value of random variable minus expected value of X.

Or, since it's a random variable, the expected value of this random variable.

So the expected value of a random variable, the expected value of a random variable is the exact same thing as the population mean.

The expected value of negative y I'll do it over here the expected value of the negative of a random variable is just a negative of the expected value of that random variable.

And we know what the expected value is, we know the expected value of this random variable is 50.

So the expected value of our random variable is equal to the sum.

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The variance of random variable y is the expected value of the squared difference between our random variable y and the mean of y, or the expected value of y, squared.

First of all, we know what the expected value of this random variable is.

And that's how you do it for an expected value of a random variable.

So the expected value of our random variable is going to be each outcome.

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If we wanted to know the expected, or if we talked about the expected value of this random variable x, that is the same thing as the mean value of this random variable x.

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It's defined as the expected value of the product of the distances of each random variable from their mean or from their expected value.