你的假设 in English translation

• your hypothesis
• your assumption
• your assumptions
• your hypotheses
• your hypothetical

Examples of using 你的假设 in Chinese and their translations into English

在你的假设中，婚姻是一团糟的，因为权力的平衡都是歪斜的。
In your hypothetical, the marriage is a shambles because the power balance is all askew.

如果你的气候在改变，意味着你所在的地区，某些天气行为可能不再适用于你的假设。
If your climate is changing, that means that certain weather behavior in your region may no longer apply to your assumptions.

如果你的假设是错误的，你要拿出一个新的方案。
If your hypothesis was wrong, you have to come up with a new one.

如果你能够提出一个合理的剧本，这表明你的假设确实还有一些问题。
If you can develop a plausible scenario, this suggests your assumption is in fact open to some question.

与其争论几个星期，你不如去测试你的假设，看看什么可行，什么不可行。
Rather than arguing for weeks, you test your assumptions and see what works and what doesn't.

GeneAnalytics可以提供高质量的信息，有利于新的发现和帮助验证你的假设，节省你的时间。
GeneAnalytics can help save you time by providing high quality information that facilitates novel discoveries and helps test your hypotheses.

如果你的假设是错误的，你就不得不再提一个新的假设。
If your hypothesis was wrong, you have to come up with a new one.

幸运的是，公开的反抗是不可能的，但是有人会开始质疑你的假设，并建议你选择其他的路线。
Thankfully, open rebellion is not likely, yet someone could begin to question your assumptions and suggest other routes to your chosen destination.

如果你的假设是正确的，那么你可以预测改进的结果，那么你离一个可以工作的程序又更近了一步。
If your hypothesis was correct, then you can predict the result of the modification, and you take a step closer to a working program.

检查你的数据，检查你的事实(这些天有所不同)，再检查你的假设。
Check your data, check your facts(there's a difference, these days), and double-check your assumptions.

一旦你创建了你的假设，你将需要测试，分析数据和形成你的结论。
Once you have created your hypothesis, you will need to test it, analyze the data, and form your conclusion.

本节指出了在决策时保持你的假设的重要性。
This section points out the importance of keeping your assumptions in mind as you make decisions.

一旦IT灾难恢复计划完成，请与业务部门负责人回顾调查结果，以确保你的假设是正确的。
Once the plan is complete, review the findings with business unit leaders to make sure your assumptions are correct.

评估统计显著性的第一步是确定你想回答的问题，并提出你的假设。
The first step in assessing statistical significance is defining the question you want to answer and stating your hypothesis.

然而，这种自由伴随着一种责任:你必须不断地反复检查你的信息和你的假设。
However, that freedom comes with a responsibility: you pretty much have to be constantly double checking your information and your assumptions.

于是，视觉化的目标变为探索：利用同样的数据，你要用图表来证实或否定你的假设。
Now your purpose is exploratory, and you will use the same data to create visuals that will confirm or refute your hypothesis.

即使你确定你理解这一状况--确定你的假设。
Even if you're sure you understand the situation- validate your assumptions.

这是关于得到下一层,关于得到你的假设正确或错误。
It's about getting the next layer, about getting your hypothesis either right or wrong.

编写多个测试用例，在理论上预想它们会以怎样的方式改变数据，并验证你的假设是否正确。
Compose several test cases with a theory of how they will transform the data, and verify if your assumptions were correct.

你可以从一个信念开始，但每个数据点要么加强要么削弱这个信念，你会一直更新你的假设。
You can start with a belief, but each data point will either strengthen or weaken that belief and you update your hypothesis all the time.