I managed to find price indexes for Norway and Netherlands going back to 1890 and compared that with the U.S.

我找到了挪威和荷兰1890年的,价格指数数据,和当时的美国作比较

耶鲁公开课 - 金融市场课程节选

This refers to random variables that have fat-tailed distributions-- random variables that occasionally give you really big outcomes.

这就表示,服从长尾分布的随机变量,这些数据出现极端值的概率比较大

耶鲁公开课 - 金融市场课程节选

So in fact, it is the case, if you look at data, and by the way, that's the way I ended up setting a lot of these parameters and playing with it, was comparing what my simulation said to historical stock data.

所以实际上，在这个例子中，如果你看到数据，顺便说一下，这就是我设置很多变量,然后编程的方式，也就是把我的仿真程序得到的结果,和历史股票数据进行比较。

麻省理工公开课 - 计算机科学及编程导论课程节选

You can take a problem that might be relatively intuitive to solve but when you scale this thing up as is increasingly the case in the web, in large data systems, and so forth, you actually have to now think smart, you actually have to think efficiently and you have to solve this problem effectively.

你可以把一个问题用比较直观的方法解决,但如果你把此类问题的数量增大,正如越来越多的互联网，和大规模数据系统中出现的问题等等,你应该考虑怎样才能更简便，怎样才能更高效,你应该用行之有效的方法处理问题。

哈佛公开课 - 计算机科学课程节选

So we're to assume we can get to any piece of data, any instruction in constant time, and the second assumption we're going to make is that the basic primitive steps take constant time, same amount of time to compute. Again, not completely true, but it's a good model, so arithmetic operations, comparisons, things of that sort, we're all going to assume are basically in that in that particular model.

因此如果我们假设在恒定的时间内,我们可以取得任何一块数据,任何一种数据结构的话,我们要做的第二个假设就是,基本的原始操作计算花费的时间是恒定的,这个假设也不是完全正确的，但这个模型其实挺不错的，因此算法操作，比较，这一类的事情，我们在这个特定的模型中都假设是基本的,操作，花费的时间是恒定相同的。

麻省理工公开课 - 计算机科学及编程导论课程节选