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Discussion
Zori started the conversation with Who in their right mind would trust their lives to an algorithm that used random methods? Xing quickly responded Everyone. At least everyone should.
Discussion
Zori started the conversation with Who in their right mind would trust their lives to an algorithm that used random methods? Xing quickly responded Everyone. At least everyone should. We routinely deal with probabilistic concepts, like getting run over by a bus when crossing the street or having a piano fall on our head. The general public is much more comfortable with notions of probability, even though they may never know the formal definition of a probability space. I for one am completely comfortable taking an airline flight if I can be assured that the probability of a disaster is less than \(10^{-20}\).
Dave wasn't biting on this topic. Instead he offered You have to be struck by the statements that it appears difficult to construct objects which you can prove exist in abundance. I wonder why this is so. Alice said We all find your brain to be a totally random thing, sometimes making sense but often not. There was laughter or at least some snickering. But after a bit, Carlos said There's something fundamental here. Maybe one could prove that there are easily stated theorems which only have long proofs. Bob blurted That doens't make any sense. Zori saw an opportunity where a client would, at considerable expense, commission her to solve a problem (at least better than the competition) that was readily understood but somehow difficult in the end. She knew about the class \(\cgN\cgP\) but maybe there were even bigger challenges (and bigger paychecks) out there.
现在轮到你 没有计算器能解决这一个问题, 但其中的碎片是可以计算的。 请在下面尝试一个, 或者输入您自己的 。
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人们对人们提出的问题
What is the difference between probability and statistics?
Probability goes from a known model to what the data should look like; statistics goes from data back to the model. Probability theory is the deductive half.
What does the law of large numbers promise?
That the average of many independent samples converges to the expected value. It says nothing about any single trial.
本页部分内容从 Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). 在这里进行浓缩和重新解释;错误属于我们。
更多 Probability Theory
Sample spaces and the axiomsRandom variables and expectationThe common distributionsThe law of large numbers and the central limit theorem