So our critical F value is 3.46.

所以我们的临界 F 值为 3.46。

And we care about a critical value of 11.07.

我们关心 11.07 的临界值。

But there's some critical value here.

但这里有一些关键值。

So we just need to figure out what this critical value is.

所以我们只需要弄清楚这个临界值是多少。

And if our value is larger than that critical value, then we can reject the null hypothesis.

如果我们的值大于那个临界值，那么我们就可以拒绝零假设。

There's some critical value here that the probability of getting a sample from this distribution above that value is only 5%.

这里有一些临界值，即从该分布中获取高于该值的样本的概率仅为 5%。

So when we look at a Z table, we want the critical Z value that they give right over here.

因此，当我们查看 Z 表时，我们需要他们在此处给出的临界 Z 值。

We're not going to look up 95%, because a Z table gives us the cumulative probability up to that critical Z value.

我们不会查找 95%，因为 Z 表为我们提供了达到该临界 Z 值的累积概率。

Or another way of saying, is this a more extreme result than the critical chi-square value that there's a 5% chance of getting a result that extreme?

或者换句话说，这是比临界卡方值更极端的结果吗？ 有 5% 的机会得到如此极端的结果？

At a critical value of 4.60, so this is 4.60, the probability of getting something at least that extreme, so that extreme or more extreme, is 10%.

在 4. 60 的临界值， 所以这是 4.60，得到至少那个极端的东西的概率， 所以极端或更极端， 是 10%。

If we look at the chi-square distribution with 2 degrees of freedom, that's this blue one over here, at a value of-- I'm trying to pick a nice blue to use-- at a critical value of 4.60.

如果我们看一下具有 2 个自由度的卡方分布，就是这里的蓝色， 其值为——我正在尝试选择一个漂亮的蓝色来使用——临界值为 4. 60。