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So first, I choose a volatility randomly, from some distribution of possible volatilities 2 from to, in this case, 0.2.
来决定的一个值，所以首先我先随机选择一个浮动值，从可能的浮动值中的分布进行选择,在这个例子中就是0。
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So it turns out that the very first one, voters are not evenly distributed is certainly true, it's undoubtedly true.
首相想到的就是,现实中选民是不均匀分布的,这的确是毋庸置疑的
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Whereas in molecular orbital theory, what I'm telling you is instead we understand that the electrons are spread all over the molecule, they're not just associated with a single atom or a single bond.
而在分子轨道理论里，我要告诉你们的时,我们任为电子分布在整个分子中,它们不仅仅是和,一个原子或者一个键有关。
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Last time we looked at the notion, last lecture we looked at the idea of a distribution.
上一次我们看过这个概念，上一次讲座中我们看到了概率分布的概念。
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That's different when you have continuous values-- you don't have P because it's always zero.
和离散型随机变量的分布不同的是,连续型随机变量的分布中,某一点的概率值始终是零
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Not only the IgG but there are special antibodies called secretory IgA and these are highly enriched in mucosal fluids in the mucus lining of your gut, and the eye, and of other--of mucosal organs.
不仅仅是IgG分子,还有一些特殊的抗体,被称作分泌型免疫球蛋白A,IgA在体内粘液中广泛存在,例如,在小肠内壁和眼球周围以及,其他带有粘膜的器官中都有IgA的分布
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With the Gaussian, there's a tail.
而高斯分布中，这边会有一个小尾巴。
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We often assume in finance that random variables, such as returns,are normally distributed.
金融学中我们常假设随机变量,例如收益率,是服从正态分布的
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We're going to assume that consumers are evenly spread along this city.
我们假设,消费者均匀分布在这个城市中
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And when we do a simulation, we're pulling the samples from some distribution.
当我们写一个仿真程序的时候，我们就是从一些分布中进行了采样。
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I'll draw something from the distribution, so this is interesting, distribution I'm now calling self dot distribution, and remember this will be different for each stock.
我会从分布中读取一个值，这就是有趣的部分，我现在会调用self。,请记住每只股票都是不一样的。
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And then we looked at this little loop before, for i in range number of stocks, I'm going to create two different lists of stocks, one where the moves, or distributions, are chosen from a uniform, and the other where they're Gaussian.
这里的这个小循环，因为i代表股票，我会建立两个不同的股票链表，一个是代表股票价格的移动，或者说是分布，它们是从均匀分布中得出的，而另一个链表是从高斯分布中得出的。
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