这篇报告中的统计数据不精确，你不应该参照他们。
The statistic figures in the report are not accurate. You should not refer to them.
人口统计学为你提供了理解和解决这些问题的工具。
Demography gives you the tools to understand and to address these problems.
通过分析几个月来流传的有关气候变化警报的消息，你会注意到令人担忧的官方统计一点点流露出来——全都是些坏消息。
Filter the news with a climate change alert for a few months, and you watch a stream of worrying official statistics trickle in - all of them bad news.
第二个是，这种通常的统计噪声来源于你试图估量一个巨大的数字就像通过两种方法得到的美国就业人数。
The second is that this is the usual statistical noise you get from trying to measure a huge number like the number of employed Americans through two different methods.
这是反复出现的在统计力学中，在很多系统中，你会有简化的极限。
And this is something that recurs in statistical mechanics, in an enormous number of systems where you have simplified limits.
重要的是，你不仅要看统计报告里面呈现的条目，而且还要看没有呈现的词语条目。
It is important to look at the terms that show up on the statistics reports as well as the words that do not show up.
统计是你最好的信息来源，前面已经解释过，信息是至关重要的。
Statistics are your best source of information, and as explained, information is critical.
你已经长时间的作为死板的数据和统计的倡议者。
你可以通过运用统计学寻找那想象中的家伙。
You can find that guy of the imagination by using statistics.
倘若时间充裕，你还可以听听你们当地学校的统计、会计或者金融学课程。
If you have enough lead-time, you can enroll in a statistics, accounting or finance class at your local university.
事情是要认识，这是一个相对的统计，因此，如果你在谈论的社会里，人们不会有很多汽车和电视，然后比例将很高。
The thing to understand is this is a relative statistic, so if you're talking about a society where people don't have many cars and TVs, then the proportion will be quite high.
如果有人在这么做，如果有人可以分辨中奖的彩票，那么你会看到的奖金总额的统计数据就会是我们现在看到的这个样子。
If there were people doing this, if there were people who could sort the winners from the losers, then what you'd see on the payout statistics is exactly what we see.
你可以在这里看看全球的统计资料。
你也可以看看可选的统计面板。
You can also look for them on the opt-in statistics dashboard.
你是不是寻找少年司机的统计数字，向他们表明你与文章中描述的“危险司机”相去很远？
Did you look up statistics on teen driving and use them to show how you didn't fit the dangerous-driver profile?
你完全是统计上的异数！
许多，也许是大多数，你读到的统计数据不是来自正规的研究，而是来自想让你看低你小弟弟尺寸的营销公司(那样的话你就会买他们的产品)。
Many, possibly most, statistics you read are not from legitimate research, but from marketing companies who want you to feel bad about your penis size (so you'll buy their product).
当然，这样叫它的话，你就不会对其中的，统计学处理感到惊奇。
Called that because, of course, you won't be surprised to learn that it's going to require a statistical treatment.
Pingdom还荟萃了其他一些有趣的统计数据，你可以在这儿看到。
Pingdom rounded up a number of other interesting statistics that you can see here.
他们也知道，大约50万到100万南非白人生活在英国，准确数字是多少，就取决于你相信谁的统计数字。
They also know that somewhere between 500, 000 and 1 million white South Africans, depending on whose statistics you believe, now live in Britain.
假如你的流量翻倍的话，那么你的收入就很有可能也会翻倍(假定你的访客的人数统计基本保持一致的话)。
If you double your traffic, you'll probably double your income (assuming your visitor demographics remain fairly consistent).
你的名字会影响你的职业生涯这种想法是否有根据？或这种想法仅为统计上的巧合？
Is there any truth to the idea that your name affects your career, or is it merely statistical coincidence?
如果你要对你的产品或系统进行正式的定量测试，你将需要更多的人以获得统计上有意义的结果。
If you want to conduct formal quantitative testing on your products or systems, you'll need more people to derive statistical results.
一个好的统计程序会为你统计好每一个登入网站的信息，你所要做的全部就是阅读那些数据并相应作出反应。
A good stats program will paint the landscape for you, and all you have to do is to be able to read the data and react accordingly.
一切取决于你如何统计碳的产出。
你可以选择不同的选项来回顾过去的统计数据。
You can select different Range options to go further back in time.
无论你的网络业务是怎样建立和运行的，通过注册用户，网站访问者，网站统计，营销模式等等，你都已经拥有了大量的信息。
No matter how your online business may be setup and running, you're sitting on a massive amount of information, through registered users, website visitors, site statistics, sales patterns and so on.
有了大量的数据，再加上运用大量不同的统计学检验方法，那么根据所使用的统计学方法的概率特性，你很容易就能发现一个重大结果。
With enough data, and by running enough statistical tests, it is easy enough to find a significant effect, given the probabilistic nature of the statistical methods used.
有了大量的数据，再加上运用大量不同的统计学检验方法，那么根据所使用的统计学方法的概率特性，你很容易就能发现一个重大结果。
With enough data, and by running enough statistical tests, it is easy enough to find a significant effect, given the probabilistic nature of the statistical methods used.
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