ZhiZhi Gewu

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ZhiZhi Gewu

Causal Diagram and Bayesian Network (Part 1)

After looking at how statistics pay little attention on causation compared with correlation, the author talks about Bayesian Network, in which he is one of the main contributors, and its relation with causal diagram. Bayes Theorem and Inverse Probability Bayes theorem provides a mathematical description of two events, the hypothesis

Two Must-Have Skills to Level Up Your SQL

Date: 26 June 2021 You may find my cheat sheet here. I used to think Python is better than SQL. In my last position, I will use Python for everything if I have the choice. Even for joining two tables, I prefer to do it in pd.merge(df1, df2,

How Statistics Became a Model-blind Data-reduction Enterprise? Sewall Wright

Wright studied genetics at Harvard. While he was working at the University of Chicago, he interested in the inheritance of coat colour in guinea pigs. He found that it is nearly impossible to breed an all-white or all-coloured guinea pig, even the most inbred families which contradict the prediction of

How Human (Sapiens) Can Coorpate in huge numbers? Telling and Believing in Fictional Stories.

Date: 20210613 We know from last time that there are at least 6 species of human 50,000 years ago. Human today belongs to a species called Sapiens. Actually, the first time Sapiens met another species, Neanderthals, we lost. Around 70,000 years ago, Sapiens started spreading everywhere around the

Human, are we alone about 50,000 ago?

Date: 20210612 Sapiens is a very popular book written by Yuval Noah Harai, on the history of Sapiens, today’s human. I am not a fan of the history book. I usually may fall asleep, not because I think history is useless. Quite the opposite, I feel history is very

Understanding Human Behaviors from the Perspective of Science │ 柯文哲台北市長

YouTube 的演算法推薦了柯文哲2015年在台大演講的錄影给我，題目是Understanding Human Behaviors from the Perspective of Science，中文譯做，從科學角度理解人類行為。看著，覺得很有趣，也富有啟發性，所以一看完就寫下一些總結。有興趣的朋友，可以去YouTube觀看：柯文哲說的生動很多，我的總結比較悶，十分推薦大家去看。人們常說，我們看到所以相信，但現實上，我們常常只看到自己相信的，甚至相信我們希望它是真的東西。怎麼解決？如何減少bias？這就是這演講的主題。 * 邏輯運算，具體就是Truth Table，什麼conjunction, disjunction, negation, conditional, biconditional * 熟度的好處就是在分析問題的時候能夠有緊密的邏輯，避免過於主觀看問題 * 當你知道越多，猜對的機率就會更高 * 這好像很廢話，但其實現實上我們往往忽略了這一步，對著問題有太多可能的原因，通過新的資訊把可能性縮小，就能得出結論

居屋2020

Date: 12/06/2021 香港的居屋，無論是一手市場還是二手市場，都是供不應求，如果你有幸抽到就好像中了六合彩頭獎一樣。最近，有家人抽到了，所以就分析一下，居屋2020的樓盤。居屋2020總共有4個新的樓盤，分別是鑽石山（啟翔苑）、火炭（彩禾苑）、馬鞍山（錦駿苑），和粉嶺（山麗苑），在收到通知時，鑽石山的樓盤已經賣得八八九九，所以就不花時間分析，但這個樓盤的確是坐落市區中心，非常不錯，這次主要想看看粉嶺的山麗苑，一個大家都覺得很遠很不方便的地方。為什麼不看火炭（彩禾苑）和馬鞍山（錦駿苑）呢？是因為火炭（彩禾苑）是單橦大廈，而且走上去要一段長斜路，離地鐵站遠，所以不考慮；而馬鞍山（錦駿苑）的確是可以考慮，但看完粉嶺（山麗苑）就覺得馬鞍山（錦駿苑）很一般。粉嶺（山麗苑）現時周邊的確是什麼也沒有，