It's the probability weighted sum of the squared distances from the mean.

它是距均值平方距离的概率加权和。

And now the notion of taking a probability weighted sum makes some sense.

现在，采用概率加权和的概念是有道理的。

But just going back, the expected value is a a probability weighted sum of each of these.

但是回过头来看，期望值是每一个的概率加权和。

Or, in a continuous distribution, you could view it as a probability weighted sum or probability weighted integral, either way.

或者，在连续分布中，您可以将其视为概率加权和或概率加权积分， 无论哪种方式。

Now we know that the expected value, the way you calculate an expected value of a random variable is you just take the probability weighted sum.

现在我们知道期望值，计算随机变量期望值的方法就是取概率加权和。

And for a discrete distribution like this, your mean or you're expected value is just going to be the probability weighted sum of the different values that your distribution can take on.

对于这样的离散分布，您的均值或期望值将只是您的分布可以采用的不同值的概率加权和。

What you have to do is say OK, each of these terms occur with some frequency or with some probability, and you kind of just take a probability weighted sum.

你要做的就是说好，这些术语中的每一个都以某种频率或某种概率出现， 你只需取一个概率加权和。

Now the way I've written it right here, you can't take a probability weighted sum of u and f-- you can't say 40% times u plus 60% times f, you won't get any type of a number.

现在我在这里写的方式，你不能对 u 和 f 进行概率加权和——你不能说 40% 乘以 u 加上 60% 乘以 f， 你不会得到任何类型的 a数字。