From the influence of the father came modern inferential statistics, which is based squarely on theories of probability.

由于" 父亲" 的影响则产生了完全于概率论原理的现代推理统计学。

And this is actually what most of inferential statistics is all about.

这实际上是大多数推论统计的全部内。

So hopefully you found that helpful, and we're going to build on this later on in some of our inferential statistics.

所以希望你觉得这很有帮助，我们将在稍后的一些推论统计中以础。

But in all of inferential statistics, I think it behooves you to become as familiar with this formula as possible.

但在所有推论统计中，我认你应该尽能熟悉这个公式。

So in a lot of what we're doing in this inferential statistics, we're trying to figure out what is the probability of getting a certain sample mean.

所以在我们在这个推论统计中所做的很多事情中，我们试图弄清楚获得某个样本均值的概率是多少。

And just so you know where we're going with this, the whole point of this is so that we can eventually do some inferential statistics about differences of means.

只是了让您知道我们的目标是什么，这就是我们最终以对均值差异进行一些推论性统计的目的。

Everything we do, or almost everything we do in inferential statistics, which is essentially making inferences based on data points, is to some degree based on the normal distribution.

我们所做的一切， 或者我们在推论统计中所做的几乎所有事情，本质上是根据数据点进行推论， 在某种程度上都是于正态分布的。

" They're extremely rational and they're much better in some ways at doing inferential learning" – using patchy information to make accurate generalisations about a messy world – " than any other creature that we know of."

“婴儿非常理性，在某些方面比我们所知的任何其他生物都更擅长推理学习”——利用零碎的信息对混沌的世界做出准确的概括。