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I'm going to define a class, and in particular, what I'm going to do, is walk through what that says.
我们碰到了一个问题，这个问题就是，我们想要建立，一个抽象数据类型。
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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。
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This could be 1979, this could be 1980, and we keep adding points so we have a whole scatter of points.
假设这里是1979年,这里是1980年,一直添加数据点,就形成了一个散点图
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He introduced the concept of electronegativity which was a measure, therefore, it is quantitative, of the atom's ability to attract electrons within a covalent bond and developed a scale of electronegativity.
他引入了电负性这一概念,一个反映着原子在成共价键时吸引电子的能力的数据标度，因此这是数量上的，在共价电子中,电子原子能吸引电子,并发展为一定规模的电负性。
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A low-level language, we used to call this assembly programming, you're down at the level of, your primitives are literally moving pieces of data from one location of memory to another, through a very simple operation.
一个低级的语言，我们曾经将其称为假设编程，你们只是处于用基本要素，把一些数据碎片,从记忆存储器的一个地方，通过简单的操作来转到另外一个地方。
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Those are the sorts of things we need to break down the statistics the billion people in poverty.
我们需要用这些事例,让人们对几十亿人口,这样一个数据有具体的认识。
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For example, one of the statistics when I talk to people about the youth online with the study that was done years ago, where they said 1/4 teenager girls had received unwelcome sexual advances on the Internet.
例如，我通过与人们交谈获得一个数据,是关于年轻人上网的一项研究,这一研究是很多年前进行的，研究显示他们称有1/4的十几岁的女孩子,在网络上受到不受欢迎的性挑逗。
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There's one particular issue with overnutrition called the metabolic syndrome that I'd like to talk about and show you a little data on.
代谢综合征是我将讨论并列举数据的,其中一个与营养过剩有关的问题
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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。
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Well, unlike the choosiness studies, here we actually have some pretty good cross-cultural data So one study, for instance, was done in 10,000 people from thirty-seven countries, ?" asking people, "Who do you want to be with?"
与伴侣选择标准研究不同，我们事实上有一些很好的跨文化数据,例如，有一个调研,以来自37个国家的1万个人为调研对象，问他们“你最想和谁在一起“
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And so when you actually have a device the bits don't flow at the speed of light in reality.
因此，当你拥有一个设备,数据位并不能以现实中的光速传输。
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I wanted to show an example with real data that I computed and that's what's up on the screen.
我用真实的数据做了一个案例,请看上方的屏幕。
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Number one, the basic structure is that you have a pointer and it points over to a pointee, but the pointer and pointee are separate and the common error is to set up a pointer but to forget to give it a pointee.
第一，基本结构是，你有一个,指向数据的指针，但是那个指针和数据,是分开的，通常错误是声明了一个指针,但是没有指向一个数据。
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And I haven't said yet, how do I get that collection, but you could certainly conceptualize that, if I had that collection, that would be nice thing to do. That is a more common pattern.
也可以这么来操作,这是个更常用的模式,这基本上也就意味着，对于某些数据的集合,我想要一个循环机制。
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Instead if we want this pointer to represent the address of something in as much as it points at that address let's just draw an arrow.
如果我们想要让这个指针表示,数据的地址，它指向的地址,我用一个箭头表示。
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If you look up in the corner of your Periodic Table on one of the sides, they have actually tabulated this for you.
你认真看一下角落上,在一个角落，应该已经为你们把数据列成表了。
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The good news is the elements in any one spot in a hash table are likely to be a small number, three, four, five.
好的一点是在哈希表中,任何一个存贮点上的元素数据是很小的,三个，四个，五个。
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Now what you're seeing here then is the beginning of complex data structures.
现在你们学习到的是复杂数据结构的,一个开始，好消息是他们之间有一个。
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There, they're just storing a database of previously solved problems.
好了，它就是一个存储之前,解决过的问题的数据库。
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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
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Somehow I've missed getting the health, but that would be another big insurance.
遗憾的是,我忘了查健康保险公司的数据了,不过那必将是另外一个巨额数字
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The other thing I have down is population, although the population of the U.S. has been pretty steady -that pink line looks awfully steady -and I have interest rates.
我还做了另外一个数据,就是人口数,而美国的人口数量一直都很平稳,粉色的那条线看起来非常平稳,我还做了利率的数据
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And, he says, give me a model for this.
然后他又说，给我一个解释这些数据的模型。
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GetFloating-- GetFloating-- GetFloat for a floating point number.
还有-,得到一个浮点型的数据，并赋给一个浮点型的指针。
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Here's a data set. There is oxygen.
这儿是一个数据集，那是氧。
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Here I'm declaring another data type altogether.
这里我声明另一个数据类型。
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We don't have data on individual city basis but it really looks like the housing collapse price collapse--that we're going through now is on a magnitude not paralleled since The Great Depression of the 1930s.
我们没有每一个城市的数据,但是看起来似乎房价真的崩塌了,价格崩塌-现在我们正经历着,自从三十年代大萧条以来,史无前例的衰退。
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So a floating point value again is a number with a decimal point, so it depends.
一个浮点型数据就是一个,带小数点的数。
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But it's just an example of, how much trouble you can get into by extrapolating.
但是这给了我们一个例子，让我们知道对数据的臆断,能给我们带来怎样的麻烦。
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It just changes one pointer to point to the same thing as another.
这只是是一个指针指向,另一个指针指向的数据。
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