So let me draw that standard normal distribution.

所以让我画出标准正态分布。

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。

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。

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 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。

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。

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。

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。

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。