如果他需要数学或科学学科的正确答案，就给他答案本。
If right answers need to be given, as in mathematics or science, give him the answer book.
她对数学的浓厚兴趣和正确的学习方法助她取得了好成绩。
Her achievements come from her strong interest in math and the right study method.
通过做正确的数学，然后可以在哪里工作，不同的岩石层。
By doing the right maths, you can then work out where the different layers of rock are.
你在何种程度上对MDD的核心意图进行了分享呢——是创建正式的模型，并且以数学的方式把模型转换为正确可执行的代码吗？
To what extent do you share the core intent of MDD - create a formal model and mathematically transform that model into correct and executing code?
第二个因素是“范围缩小“：用数学术语讲，正确的答案集中在群的边缘。
The second effect was “range reduction”: In mathematical terms, correct answers became clustered at the group's edges.
他们完全正确。你不需要了解很多数学你就能做个很棒，很专业的程序员。
They're absolutely right. You can be a good, solid, professional programmer without knowing much math.
副作用把验证程序正确的数学问题复杂化。
Side effects complicate the math required to prove program correctness.
为了使用户负载与正确的尺度相关，您需要理解应用程序是如何利用后端资源的，这实际上是一道数学练习题。
Correlating the user load to the appropriate metric requires understanding how the application is utilizing backend resources, and becomes an exercise in mathematics.
但直到有人找到一种可信的数学证明之前，这样的结论正确与否依然有待商榷。
But until someone provides a sound mathematical proof, the validity of the assumption remains open to question.
庞加莱猜想的重要不仅在于它的实际应用性，还因为巨量的数学工作是基于假定庞加莱猜想是正确的。
Poincare's conjecture is important not for its practical applications, but because a vast quantity of mathematical work assumes that it is true.
一方面来说，一份论文最重要的事情之一（当然不是唯一重要的事情）是如数学计算般给出最终的答案，并证明答案是正确的；
On the one hand, one of the most important things in mathematics (though certainly not the only thing) is to get results, and prove them correctly.
“我们认为它们是非常相似的两样东西，”28岁的助理教授埃里克在谈及数学与艺术时说，“它们都需要创作过程，而且都有关于正确的观念。”
"We view them as very similar things," says Erik, a 28-year-old assistant professor, referring to math and art. "They're both creative processes."
但他们的数学模型假定市场价格总是正确的。
But their mathematical model assumes the prices in markets are always correct.
Fukuyama看起来比较正确的把握了这种偶然性的理论，但是我想他错误的认为这种偶然性不可能被一种更系统的，甚至数学的，的框架来描述。
Fukuyama seems quite correct to grasp for this type of contingent theory, but I think he is wrong to believe that it cannot be formulated much more systematically, even mathematically.
尽管滥用数学术语的情况如此普遍，但有一件事最为离奇——当真的需要讨论数字时，经理们全都支支吾吾起来，正确的数字术语一个都不见了。
The strangest thing about all this misuse of mathematics is that when there is an actual need to discuss figures, managers go all coy, and proper numerical terms are nowhere to be seen.
第二，如果这个数学模型是正确的，一些其他的作用也可能把氢气拉(推)到地表。
Second, if the model is correct, some other process could be pulling (or pushing) hydrogen toward the surface.
例如您的孩子每周花五天、每天花两小时学习数学，可成绩仍不理想，那么您就要和孩子重新评估这种学习方法是否正确。
For example, if your son studies for a math test for two hours a day, five days a week, yet gets a bad grade, then you and your son need to reevaluate his math studying regimen.
学校里教数学的方式都错了。仅仅是教学的方法错了，不是教数学本身错。如果你以正确的方式学习数学的话，你会学的更快，记住这点，对你，作为一个程序员来说很有价值。
Way, way wrong. If you teach yourself math the right way, you'll learn faster, remember it longer, and it'll be much more valuable to you as a programmer.
最后，我们所有的层合并使用合成数学正确混合在一起的一切。
And finally, combine all our layers using compositing math to correctly mix everything together.
正确学习数学的方法是广度优先，而非深度优先。你需要生存在空间里，学习事物的名字，区分出什么是什么。
The right way to learn math is breadth-first, not depth-first. You need to survey the space, learn the names of things, figure out what's what.
毫无疑问，返回的比赛是 Race_01，从数学和字母角度来说都是正确的，26.2大于 13.1。
Sure enough, the race that comes back is Race_01, which is correct: 26.2 is greater than 13.1, both mathematically and lexicographically.
你了解吗？他们完全正确。你不需要了解很多数学，你就能做个很棒，很专业的程序员。
And you know what? They're absolutely right. You can be a good solid professional programmer without knowing much math.
你了解吗？他们完全正确。你不需要了解很多数学，你就能做个很棒，很专业的程序员。
And you know what? They're absolutely right. You can be a good, solid, professional programmer without knowing much math.
你了解吗？他们完全正确。你不需要了解很多数学你就能做个很棒，很专业的程序员。
And you know what? They're absolutely right. You can be a good, solid, professional programmer without knowing much math.
但是霍夫特(GerardtHooft)说两位数学家的结论是正确的——但他宁愿选择决定论而不是自由意志。霍夫特是荷兰utrecht大学的物理学家，曾获1999年的诺贝尔物理学奖。
But Gerard 't Hooft of the University of Utrecht in the Netherlands, who won the Nobel Prize in physics in 1999, says the pair's conclusions are legitimate - but he chooses determinism over free will.
如果你以正确的方式学习数学的话，你会学的更快，记住这点，对你，作为一个程序员来说很有价值。
If you teach yourself math the right way, you'll learn faster, remember it longer, and it'll be much more valuable to you as a programmer.
如果我们按照数学做出正确的决定，我们将会获胜，犯更少的错，来赢更多的钱。
If we make the right mathematical plays, we will triumph, making more money through less mistakes.
如果我们按照数学做出正确的决定，我们将会获胜，犯更少的错，来赢更多的钱。
If we make the right mathematical plays, we will triumph, making more money through less mistakes.
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