This problem is an example of conditional probability.
这个问题是条件概率的一个例子。
单词 | Conditional probabilities |
释义 |
Conditional probabilities
原声例句
双语版 TED-Ed 演讲精选 This problem is an example of conditional probability. 这个问题是条件概率的一个例子。 双语版 TED-Ed 演讲精选 This is how conditional probability works. 这就是条件概率。 双语版 TED-Ed 演讲精选 And conditional probability isn't just the stuff of abstract mathematical games. 条件可能性并不只是抽象的数学游戏。 TED-Ed(视频版) If you're wondering how this could possibly be right, it's because of something called conditional probability. 如果你在想这怎么可能是正确答案,是因为条件可能性。 双语版 TED-Ed 演讲精选 This is known as the conditional, or posterior probability, determined once the possibilities have been narrowed down through observation. 这被称为条件概率或后验概率,一旦通过观察缩小了可能性就足以确定了。 TED-Ed(视频版) Computers and other devices use conditional probability to detect likely errors in the strings of 1's and 0's that all our data consists of. 电脑和其他的装置会使用条件可能性在1 和 0 中 来侦测我们数据中的潜在错误。 经济学人-文艺 “The Cartoon Guide to Statistics” promised readers they would chew over binomial distributions and conditional probability with the same ease with which they enjoyed Spider-Man. 那年一本名叫《统计学卡通指南》的书,承诺可以让读者津津有味地学习二项分布和条件概率,就像阅读《蜘蛛侠》一样轻松愉快。 202322 Conditional Probability: The probability of an event given that another event has already occurred. 条件概率:给定另一个事件已经发生的事件的概率。
中文百科
条件概率 Conditional probability(重定向自Conditional probabilities)
![]() 本文定义了表征两个或者多个随机变量概率分布特点的术语。 条件概率(英语:conditional probability)就是事件A在另外一个事件B已经发生条件下的发生概率。条件概率表示为P(A|B),读作“在B条件下A的概率”。 联合概率表示两个事件共同发生的概率。A与B的联合概率表示为 边缘概率是某个事件发生的概率。边缘概率是这样得到的:在联合概率中,把最终结果中不需要的那些事件合并成其事件的全概率而消失(对离散随机变量用求和得全概率,对连续随机变量用积分得全概率)。这称为边缘化(marginalization)。A的边缘概率表示为P(A),B的边缘概率表示为P(B)。
英语百科
Conditional probability 条件概率(重定向自Conditional probabilities)
![]() ![]() ![]() ![]() In probability theory, conditional probability is a measure of the probability of an event given that (by assumption, presumption, assertion or evidence) another event has occurred. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(A|B), or sometimes PB(A). For example, the probability that any given person has a cough on any given day may be only 5%. But if we know or assume that the person has a cold, then they are much more likely to be coughing. The conditional probability of coughing given that you have a cold might be a much higher 75%. |
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