ZhiZhi Gewu

Sign in Subscribe

Books

How Randomized Controlled Trial Deconfounds the Confounding Bias

What is confunding bias? Imagine you are a farmer trying to determine applying fertilizer A to the field will increase the yield of crops. In other words, you are trying to establish a causal relationship between fertilizer A and yield. Our tricky Nature tells you that the effect of the

Causal Diagram and Bayesian Network (Part 2)

There are three building blocks of Baysian Network. Remember that a Bayesian Network is nothing but some arrows connecting with different nodes representing the conditional probability table. The so-called building blocks are just the three types of arrow patterns. Arrow PatternEasy To RMB NameDescriptionA –> B –> CChainFire ->

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

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

How Statistics Became a Model-blind Data-reduction Enterprise? Karl Pearson

In the last blog post, we have covered Francies Galton and his Galton Board. In this post, we will talk about Karl Peason. Pearson was affected by Galton’s idea on correlation. He believes correlation is bigger than causation. Causation was reduced to nothing more than a special case of

How Statistics Became a Model-blind Data-reduction Enterprise? Francies Galton.

Date: 5 June 2021 This is Chapter 2 of the book, The Book of Why. This chapter is an account of the history of statistics and how it departs from understanding causation to only correlation. I personally did not validate the accuracy and completeness of the stories in the Chapter.