the book of why
To better understand this article, you need to first read these two articles: Causal Diagram and Bayesian Network (Part 2) How Randomized Controlled Trial Deconfounds the Confounding Bias A confounder is like some backdoor paths from X to Y. To eliminate the confounder, you just need to block those backdoor
the book of why
Before talking about how confounding should be defined, let’s talked about how it was defined before. Some declarative defintions A confounder is any variable that is correlated with both X and Y. A confounder X and Y is a variable Z that is (1) associated with X in the
the book of why
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
the book of why
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 ->
the book of why
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
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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
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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
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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
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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.
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Date: April 27, 2021 This chapter is not about how to develop a scorecard. Rather, it focuses on the key steps, resources needed, and evaluations a manager should know. I have written two summaries on scorecard development which covers most of the points in this chapter, especially on the key
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I became a fan of Ray Dalio after reading his book, The Big Debt Crisis and his article series on LinkedIn called The Changing World Order. I was really impressed by his knowledge. Then I picked up another popular book written by him called Principles. It is a long book.
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Date: April 25, 2021 This chapter, although it is called Planning Consumer Products, I think it is about product development. It talks about the variables in developing a product/ adjusting a product. First of all, the product should align with the underlying strategy of an organization. We need to understand