So let me draw that standard normal distribution.

所以让我画出标准正态分布。

For a normal, or a standard normal distribution, place the following in order from smallest to largest.

对于正态或标准正态分布，请按从小到大的顺序放置以下内容。

Well, by definition, the standard deviation for the standard normal distribution is 1.

那么，根据定义，标准正态分布的标准差为 1。

And this is a standard normal distribution, so the mean, or you can kind view the center point right here.

这是一个标准的正态分布，所以平均值，或者你可以在这里查看中心点。

And then it has a negative kurtosis, which means that it has shorter tails and smaller peaks than a standard normal distribution.

然后它有一个负峰度，这意味着它比标准正态分布有更短的尾巴和更小的峰。

And let's define it as the sum of 3 of these independent variables, each of them that have a standard normal distribution.

让我们将其定义为 3 个自变量的总和，每个变量都服从标准正态分布。

Because if you are sampling just once from this standard normal distribution, there's a very high likelihood that you're going to get something pretty close to 0.

因为如果你只从这个标准正态分布中抽样一次，你得到的值非常接近于 0 的可能性非常高。

Let me define a new random variable Q that is equal to-- you're essentially sampling from this the standard normal distribution and then squaring whatever number you got.

让我定义一个新的随机变量 Q，它等于——你实际上是从这个标准正态分布中抽样，然后对你得到的任何数字进行平方。

So a standard normal distribution is one where the mean is-- sorry, I drew the standard deviation-- is one where the mean, mu for mean, is where the mean is equal to 0, and the standard deviation is equal to 1.

因此， 标准正态分布的均值是— — 抱歉，我画了标准差— — 均值 mu 表示均值等于 0， 标准差等于 1。