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Homer was in error, Milton told us, and Milton called on the moral voice of Spenser to help him make that moral judgment against Homer.
弥尔顿告诉我们荷马错了，他还要求斯潘塞的道德之声,帮助他做出反对荷马的道德判断。
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Error is not a poetic elaboration on things which somehow, as it does in Plato's view, undermines the integrity of that truth identified by philosophers.
错误并不是对事物一种诗化的详细阐释，正如柏拉图的观，这种阐释以某种方式削减了，被哲学家认同的真理，的诚实性。
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I've learned that with high probability, the error is not in the first part of the program.
我从这一点得到了什么？,我得到的是错误有很大的可能。
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Like Milton's Sin, Spenser's Errour is half woman, half serpent, and in a lot of ways she embodies the very problem of religious error.
像弥尔顿笔下的罪恶之神，斯潘塞笔下的“错误“是一位，一半女人一半毒蛇的怪物，她从各个方面具体化了宗教错误。
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So generally, if you don't get an error message in a command line environment like this, that's good.
一般来说，如果你在命令行界面,没有收到错误信息，那就是好消息。
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If you go onto some of the other foods in here you see that the error became even greater in some of these cases.
如果你们看表上的其他一些食物,一些例子的估算误差会更大
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So, it depends on your error bar in a sense.
因此，从某种意义上说它取决于误差棒。
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It's thought that that is a serious error because it destroys trust in the currency.
这被认为是一个严重的错误,因为它会摧毁人们对货币的信任程度。
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They plug it in and make a keystroke error right off the bat.
乘完了,正好砸出击是出了一个按键错误。
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It can be 5 dollars minus your error in pennies, if you won.
如果你赢了就是五美元减去你的误差
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In this case it says, this is a syntax error, and it's actually highlighting where it came from so I can go back and fix it.
在这个例子中它显示这是个语法错误，并且会高亮显示它的位置,以便于我去修改。
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Before I type in that expression, I get an error, right?
在我输入表达式之前，出现一个错误，对吧？
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That says it's in here. It's in this tri-block. It raised an exception, but it wasn't and I O error.
这在这里它是一个try程序块,它报出异常，但他不是io错误。
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As a consequence, there's a lot of variability and error in these dietary measurements.
结果就是,饮食测评中会有很多变数,和误差
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So that's a big percentage error here and it was in the people's favor.
由于人们的一厢情愿,造成巨大的误差
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By the way, here's where the average error is in this particular study.
顺便一提,这是这个实验的平均误差值
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So for all these reasons there's some error in this kind of thing.
以上种种原因,造成了研究中的误差
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And each time one of these errors occurs, or you get multiple errors that compound each other, then you've got a lot of potential error introduced in these messages.
每当有误差发生,或多重误差复合叠加,然后你所得到的信息,就会包含很多潜在的误差
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That's the hope, but of course, there's still error in that.
这便是所要的,但当然,其中仍然会有误差
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In other words, truth arises out of error.
换句话说，真理在错误之上出现。
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Let's go the other direction. And yes, I guess I'd better say s not 2, or we're going to get an error here. Again, in twenty-three checks.
这里我得说不能是2，否则要报错了，再一次，调用了23次,在这个例子里，它从尾部开始。
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And this, in my mind, should have been an error.
这个地方我认为应该是一个错误。
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Second, it shows that it-- it weakens to some extent how much faith we can have in studies that link diet to health because of this error that gets introduced.
第二,表明了这在某种程度上消弱了,我们在研究饮食与健康之间联系时的信心,因为误差的出现
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Now this is a little counterintuitive, because very often people underestimate the amount of calories in things, but what's important here is the-- the error, the size of the error.
这与我们的直觉有些相反,因为经常性地,大家低估了卡路里含量,重要的是,误差和误差的大小
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Way back in nineteen-eighty-two, we did a study on this, and then I'm going to show you some similar studies that have been done in subsequent years to show you how much the error is.
回到1982年,我们做了一个这样的实验,你们将看到一些类似的实验,是在随后几年中做的,向你们证明误差有多大
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You figure that most of those boxes are being eaten by somebody or another, there's some waste that you might calculate in, but there--error gets introduced there trying to estimate that, so you get a number on that.
你的计算中大部分食品,都被人们吃了,浪费的那些也要计算进来,但其中的误差,也要估算出来,最后得出一个数字
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For example, you can bring people into a lab or something like that and show them food and say, well can you estimate how many calories are in this, and you actually know how many calories are in it, and you get the error.
比方说,带一些实验对象进入实验室,向他们展示一些食物并问,你们能估计这些食物含有多少卡路里吗,人们认为自己对卡路里含量心里有谱,但他们错了
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Highly educated people, a lot of you probably care a lot about food, think about labels, read them and things like that, not one person out of the 300-350 people in this room guessed correctly within ten percent margin of error.
你们受过高等教育,注意饮食健康,关注食品标签,等等,在10%的误差幅度下,在300-350个人中,没有一个人估计正确
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