Workbook for Volume 1 – Part II – Section #18: The “Causal Revolution” Works as a “Repair Program”
For new readers: Please read the “Pinned Post” at the top of this Substack’s Home Page, and titled Why Use Public Peer-Review to Write a Book? - “See for Yourself”.
For returning readers and subscribers: This post introduces the Revised Version for Volume 1 – Part II – Section #18: The “Causal Revolution” Works as a “Repair Program”
Summary:
Section #18: The “Causal Revolution” Works as a “Repair Program” – This section discusses the origins of Judeal Pearl’s “Causal Revolution”, and how it turned into a “Repair Program” for the Logic & Statistics Program. As shown in the table below, it addresses the assumption of “As-if” models based on associations between “Random Variables”. The Logic & Statistics Program operates at the level of population & sample averages, and statisticians emphasize that correlation is not causation. However, individuals making “Predictions” to guide their “Motions” interpret data, implicitly or explicitly, based on a causal understanding of the physical world. This difference between statistics and causality creates a space for paradoxes, such as Simpson’s paradox that cannot be resolved with statistical methods. Pearl’s “Causal Revolution” moves us from the abstract “As-if” models of the Logic & Statistics Progrem to concrete “Process” models that can generate counterfactual scenarios as a basis for informed individual, business and investment decisions. We see what we understand, and we understand what we name. Causal queries cannot be answered, or even articulated in the traditional language of statistics. Statistics describes the data, not the “Process” responsible for the data. Pearl gives us new names to see causal “Processes”. The Logic & Statistics Program focuses on finding pithy mathematical descriptions of the joint distribution of a set of “Random Variables”, or specific parameters of such distribution. However, to move beyond the summarization of data, statistical inference must think carefully about causal questions. Causal models reveal themselves through patterns of statistical “Puzzles, Paradoxes & Anomalies” created by confounding variables. Pearl’s Causal Revolution becomes a “Repair Program” of the Logic & Statistics Program because it provides “Tools” to make better individual, business and Investment decisions.
Developing…
”CTRI by Francois Gadenne” writes a business book in three volumes, published serially on Substack for public peer-review. The book connects the dots of life-enhancing practices for the next generation, free of controlling algorithms, based on the lifetime experience of a retirement age entrepreneur, & continuously updated with insights from reading Wealth, Health, & Statistics research papers on behalf of large companies as the co-founder of CTRI.