prior and posterior
collocation先验与后验（贝叶斯推断中的两个核心概率）
Bayesian statistics works with the prior and the posterior.
贝叶斯统计处理的是先验和后验。
后验概率
先理解核心含义，再看它在真实句子里的用法。
后验概率
The probability that a hypothesis is true, as calculated by Bayes' theorem.
The doctor examined the patient's posterior for any signs of injury.
医生检查了病人的臀部是否有受伤的迹象。
假设为真的概率(按贝叶斯定理计算)。
The probability that a hypothesis is true (calculated by Bayes' theorem).
She fell off her bike and landed on her posterior, causing a bruise.
她从自行车上摔下来，屁股着地，造成了瘀伤。
The horse's posterior was muscular and well-defined.
这匹马的后部肌肉发达，轮廓分明。
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先验与后验（贝叶斯推断中的两个核心概率）
Bayesian statistics works with the prior and the posterior.
贝叶斯统计处理的是先验和后验。
计算后验概率
To make predictions, you first compute the posterior.
为了做出预测，你首先要计算后验概率。
更新后验（根据新数据重新计算后验）
Each new observation allows us to update the posterior.
每一条新观测都使我们能够更新后验。
估计后验分布
We estimated the posterior using a Markov chain Monte Carlo method.
我们使用马尔可夫链蒙特卡罗方法估计后验分布。
从后验中抽样
It is often easier to sample from the posterior than to compute it exactly.
通常从后验中抽样比精确计算后验更容易。
今天的后验将会是明天的先验。
This saying, often attributed to the statistician Dennis Lindley, captures how Bayesian inference keeps updating our beliefs as new data arrive.
这句常被归于统计学家丹尼斯·林德利的话，概括了贝叶斯推断如何随着新数据的到来不断更新我们的信念。
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记忆：posterior 开头像 post（后），贝叶斯公式算完之后得到的概率就是后验概率。
语域：formal 常见场景：贝叶斯统计、数据分析、机器学习 后验概率是贝叶斯统计中的专业术语，多用于统计学、机器学习和数据分析等学术或技术语境；日常英语中较少使用这个含义。
该名词通常用于解剖学或正式语境。
Dictionary facts from ECDICT, WIKTIONARY, WORDNET.