So the test on the left, you'll remember, was the one with test one, I believe, was the uniform distribution, and test two is the Gaussian.
所以左边的测试,你得记得就是均匀分布,而第二个测试是高斯分布。
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
With a different volatility for the stocks because that was also selected randomly, plus some market bias.
或者均匀分布的一个随机值,因为数值选择上的随机性,再加上市场偏好。
So, if I've got positive charge uniformly distributed, look at the choice. It's a brilliant experiment.
所以如果按照正电荷是均匀分布的假设来说,就会是这样的,这是一个聪明的实验。
It could be non-spacially constant.
空间分布也不均匀。
That is, if you plot the relationships between people We can take each person in this room, find everybody you know and who knows you and draw a line, but if we were to do this you wouldn't find an even mesh of wires.
也就是说如果要划出人们之间的关系,例如这个教室里的人,把互相认识的人用线划出来,如果我们这样做,得到的结果不是一个分布均匀的网状图。
So one thing that seems odd about the way we set up this model is that the voters are not evenly distributed.
有一点使我们建立此模型的假设很牵强,即是选民们不是均匀分布的
STUDENT: The variance of the Gaussian seems to be less than the variance of the uniform.
学生:高斯分布的变化比,均匀分布的变化小。
But if you think about it, it would not be surprising if the Gaussians, at least, gave us some surprising, more extreme, results, than the uniform.
但是如果你去思考,你不会惊讶高斯分布,会给我们的答案会,比均匀分布大。
Or it could be uniform, where every value was equally probable.
还有均匀分布,每个值都有相同的可能性。
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
This can't make sense because the plum pudding model says you've got uniformly distributed charge.
这是讲不通的,因为布丁模型说的是电荷在里面均匀分布。
Because, if you look at this molecule, you say that, well, the electrons are a little bit closer to the right than to the left so the charge is not uniformly distributed.
因为,你看到这分子时,因为,你看到这分子时,对更偏向右边,它的电荷一定不是均匀分布的。
And think about, what's the difference between the Gaussian and the normal?
高斯分布和均匀分布的,差别是什么?
I'm going to say that the positive charge is not uniformly distributed.
我要说,正电荷不是均匀分布的。
Because the uniform, as we've set it up here, is bounded.
因为我们在设定的时候均匀分布,是有界的。
And then I'll create this function, d1 this distribution d 1, which will, whenever I call it, give me a random, a uniformly selected value between minus and plus volatility.
然后我会创建这个函数,这个概率分布,每次我调用这个函数的时候,他会给我返回一个随机的,按照均匀分布,从正负浮动值之间选择的值。
The voters are not evenly distributed 10%, 10%, 10%.
每个立场的选民并非按10%均匀分布
A random-- a uniform, and a Gaussian.
一种随机的一种均匀分布和一种高斯分布。
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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