And all the random variables of interest are now to be normal.

所有感兴趣的随机变量现在都是正态的。

So X is a random variable that's uniform over a certain range.

所以X是一个在一定范围内均匀的随机变量。

This is a real random variable mean.

这是一个真正的随机变量均值。

And then if we had another random variable, another chi-squared distributed random variable-- so then we have, let's say, Q3.

然后， 如果我们有另一个随机变量， 另一个卡方分布随机变量— —那么我们就有了， 比方说， Q3。

So you do the same thing with this with random variable y.

所以你用随机变量 y 做同样的事情。

But they needed to introduce a random variable to prove causality between the adoption of robots and the effects on staffing.

但他们需要引入一个随机变量来证明机器人的采用与对人员配备的影响之间的因果关系。

Let's do the same thing for random variable y.

让我们对随机变量 y 做同样的事情。

But with that said, let's think about the sampling distributions of each of these random variables.

但话虽如此，让我们考虑一下这些随机变量中每一个的抽样分布。

This is way different from every other social media because most of your connections on those platforms are based on location, school, work, or other random variables.

这与其他社交媒体截然不同，因为你在这些平台上的大多数联系都是基于地点、学校、工作或其他随机变量。

But here, we're talking about y, random variable y.

但在这里，我们谈论的是 y，随机变量 y。

Or another way to view it is if I wanted to take, let's say I have some other random variable.

或者另一种查看方式是，如果我想采用，假设我有一些其他随机变量。

It's a little different, because I'm actually doing it with two different random variables.

有点不同，因为我实际上是用两个不同的随机变量来做的。

And I'm doing it with two different random variables for a reason.

我用两个不同的随机变量来做是有原因的。

That sample mean is a random variable.

该样本均值是一个随机变量。

Because now I'm going to define a new random variable.

因为现在我要定义一个新的随机变量。

So we just showed you is that the variance of the difference of two independent random variables is equal to the sum of the variances.

所以我们刚刚向您展示了两个独立随机变量之差的方差等于方差之和。

And we know that this is going to be the same thing as the population mean for that random variable.

我们知道这与该随机变量的总体均值相同。

So the expected value of these squared differences, and that you could also use the notation sigma squared for the random variable x.

所以这些平方差的期望值，你也可以使用符号 sigma squared 来表示随机变量 x。

So if I want the probability of this random variable right here being greater than 2.41, or its p value, we read it right here.

因此，如果我希望这里的这个随机变量的概率大于 2.41 或其 p 值，我们就在这里读取它。

We have the covariance of these two random variables.

我们有这两个随机变量的协方差。