So, more data to come, so this is a clip some of you might have seen in section already.
随着更多数据的出现,就会形成一个标签,有些人可能已在相应章节中看到过了。
And the figure was that some 2,000 people die as a result of accidents each year using cell phones.
数据显示每年有2000人左右,因开车时使用手机,而死于车祸。
And it is a stereotype but it's a statistically robust one and nobody lines up to protest this.
这确实是刻板印象,但这是有数据支持的,而且没有人会排队去抗议它。
We came up with this idea that we open up the interface so that people who owns the data, who owns the content, can submit it to us and we will integrate into our search results.
于是我们有了一个想法,开放一个接口,让拥有数据,以及容量的人,能够将其提交给我们,然后整合到搜索结果中。
In our--in this particular study we had some people estimate things low and some people estimate things high, but overall, this--these would represent overestimates.
在这个实验中,有些人低估了,而有些人高估了数据,但总体来说,结果显示人们高估了数据
Again, I don't want to make too much of my estimates because different people would estimate these things in different ways, but that's the theory.
再说一次,我不想太过强调我的估算,因为不同的人,会用不同的方法估算这些数据,但这只是个理论。
I just wanted to show you this last graph, or this last set of statistics to go from causes of death in the U. S.
我想让你们看的最后一张图,或者说最后一组统计数据,不是关于美国人的死因
At least if we look at the statistics, just about every single one of you, after you leave Harvard,will join an organization, an organization that is a social enterprise, not for profit,something to better the world.
看一下统计数据,你们每个人,离开哈佛后,都将加入公司,这个组织是个社会企业,非盈利机构,只为贡献社会而存在的。
So, for example, if you're the kind of person, which is I have to say all I ever was, if you're the kind of person who can kick the ball fairly hard but not very accurately, then it actually might change these numbers.
比如你是这样的一种人,我也不得不承认我以前也是这种人,如果你是那种能够大力抽射,但是精准度不高的人,那这些数据对你就不太准了
London, already by the late sixteenth century, one-sixth of all the people, I think this is E.A. Wrigley who pointed this out a long time ago--one-sixth of all the people in England went to London frequently, because London was absolutely gigantic as a city.
伦敦,早在十六世纪后期,六分之一的人口,我想是E.A莱格力很久以前给出的这个数据,他指出,当时有六分之一的英国人,会经常去伦敦,因为伦敦当时是个巨型城市
So, they started to do collecting of data on mortality and they developed something called actuarial science, which is estimating the probability of people living.
他们开始收集死亡率的数据,并且发展出精算学,用来估算人在各年龄段死亡的概率
One question that comes up is that maybe-- this is for the U.S. data-- and some people say, well, maybe, why are we looking at the U.S.?
这又产生了一个新问题,这是采用美国市场的数据得出的结果,有些人会问,为什么光研究美国市场呢
These numbers are very discouraging.
这些数据的确很让人泄气
Well, a cross-sectional study would mean that you'd get a random group of the population and measure them in 1970 and then take another random group five years later and measure them, but it wouldn't be the same people necessarily, it would be different groups of people.
那么,横断面研究就是,1970年你在人群中随意选择一组人,并记录下相关数据,然后,五年后再随意选择一组人记录数据,但这不需要是同一组人,通常是不同的人
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