It'll take you from knowing nothing to being able to fully apply Bayes' theorem or multiple linear regression.

它将带你从一无所知到能够完全应用贝叶斯定理或多元线性回归。

For this case, we do have a Bayes rule, once more.

对于这种情况，我们再次有贝叶斯规则。

I think that's what this notation says, but we don't see so clearly Bayes' theorem.

我认为这就是这个符号所说的，但我们没有那么清楚地到贝叶斯定理。

So this plot is meant to show usage of Bayes.

所以这个图是为了展示贝叶斯的用法。

The logic there is completely the same but the Bayes factor  that you compute is going to look different.

那里的逻辑完全相，但你计算出的贝叶斯因子会不。

Bayes's theorem is crucial for everything from the scientific method to evaluating legal evidence and progress in artificial intelligence.

贝叶斯定理对于从科方法到评估法律证据和工智能的进步等一切都至关重要。

Soon, Bayes got a tip that a horse fitting White Stockings' description was stabled at a tavern in Whitechapel.

很快，贝叶斯得到线索，一匹符合怀特·斯托克林描述的马被安置在怀特柴泼区的一家酒馆里。

When did we start calling it Bayes?

我们什么时候开始叫它贝叶斯?

Wo taking this more honest representation of it,   let's compare our two versions of Bayes rule.

好吧，让我们采用这个更诚实的表达方式，比较一下我们两个版本的贝叶斯规则。

And he wrestled with this and he came up with a little bit of mathematics that we now call Bayes' theorem.

他为此进行了思考，并得出了我们现在称为贝叶斯定理的一点数成果。

I was reading through a Bayes book that carried through this argument about the prosecutor's fallacy.

我正在阅读一本贝叶斯的书，这本书贯穿了关于检察官谬误的论点。

What that would mean is that our  Bayes factor is 90 instead of 10, the test is doing more work for us.

这意味着我们的贝叶斯因子是90而不是10，测试为我们做了更多的工作。

Each answer to that question gives you a new Bayes factor, a new thing that you multiply by your odds.

这个问题的每个答案都会给你一个新的贝叶斯因子，一个你乘以你的赔率的新东西。

Now let's contrast this  with the usual way that Bayes rule is written, which is a bit more complicated.

现在让我们将这与通常写的贝叶斯规则进行对比，后者稍微复杂一些。

In our example this number is 10. This is the Bayes factor, also sometimes called the likelihood ratio.

在我们的例子中， 这个数字是10。 这是贝叶斯因子，有时也称为似然比。

It's very commonly used to introduce the topic of bayes rule in  probability.

它经常被用介绍概率中的贝叶斯规则话题。

So a discussion of vaccine safety proceeds to Bayes's theorem, a procedure for refining one's judgment of probabilities as new evidence comes to light.

因此， 疫苗安全性的讨论将涉及到贝叶斯定理，这是一种随着新证据的出现而完善概率判断的程序。

The reason I don't like using this notation in general, even though I can see Bayes' Theorem, is that bar usually means given.

即使我可以到贝叶斯定理，我通常不喜欢使用这种表示法的原因是 bar 通常表示给定。

In the context of Bayes' theorem, this value also has a special name, it's the " likelihood" .

在贝叶斯定理的背景下，这个值也有一个特殊的名称，它是“似然”。

But with the other formula, to do that you have to recompute everything each time, you can't  leverage a pre-computed Bayes factor the same way.

但是用另一个公式， 每次你都得重新计算所有内容，你不能像那样利用预先计算好的贝叶斯因子。