统计
Everything Is Predictable: How Bayes' Remarkable Theorem Explains the World Goodreads
作者: Tom Chivers publishing house: Weidenfeld & Nicolson 2025 - 4
2026年6月23日 已读
应用统计学基础的(不能更)通俗解读,很佩服,很欣赏。一个数学家为了给大众讲明白贝叶斯和基本数理逻辑,连公式都不要了开始画画片,你就知道他在多么努力地讲这个事。一本通俗科普书里看到小10页的引用,也能知道作者拿这个当个事儿来写。

前2/3是通俗统计学,后1/3就是通俗哲学,人人都是贝叶斯驱动带着先验看世界,基于统计学的科学页不是全知的(当然也不是完全无知)。由繁至简,很多比方我都很喜欢,比如老人为什么富有智慧也难于变通,因为新世界的变化需要新的经验形成先验。

但看见作者暗炫自己姥爷是凯恩斯这事……who tm cares啊我说……
科普 统计 pop science
The Book of Why Goodreads 豆瓣
6.8 (10 个评分) 作者: Judea Pearl / Dana Mackenzie publishing house: Basic Books 2018 - 5
A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence
“Correlation is not causation.” This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality–the study of cause and effect–on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl’s work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.