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Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.
Causality: Models, Reasoning, and Inference (2000; [1] updated 2009 [2]) is a book by Judea Pearl. [3] It is an exposition and analysis of causality. [4] [5] It is considered to have been instrumental in laying the foundations of the modern debate on causal inference in several fields including statistics, computer science and epidemiology. [6]
Rubin defines a causal effect: Intuitively, the causal effect of one treatment, E, over another, C, for a particular unit and an interval of time from to is the difference between what would have happened at time if the unit had been exposed to E initiated at and what would have happened at if the unit had been exposed to C initiated at : 'If an hour ago I had taken two aspirins instead of ...
The Book of Why: The New Science of Cause and Effect is a 2018 nonfiction book by computer scientist Judea Pearl and writer Dana Mackenzie. The book explores the subject of causality and causal inference from statistical and philosophical points of view for a general audience.
[2] The book primarily applies lessons from regression-oriented analysis to qualitative research, arguing that the same logics of causal inference can be used in both types of research. [3] [1] The text is often referred to as KKV within social science disciplines. The book has been the subject of intense debate among social scientists.
Granger defined the causality relationship based on two principles: [8] [10] The cause happens prior to its effect. The cause has unique information about the future values of its effect.
What If? is Munroe's second published book, his first being XKCD: Volume 0, a curated collection of xkcd comics released in 2009. [12] Munroe released a third book, titled Thing Explainer, in 2015, and a fourth book titled How To in 2019. [13] [14] A sequel, What If? 2, was announced in January 2022 and was released on September 13 that year. [6]
Unlike descriptive statements (e.g. "the average height in the US is X"), causal statements involve a comparison between what happened and what would have happened absent an intervention. The latter is unobservable in the real world, a fact that Holland & Rubin term "the fundamental problem of causal inference" (pg. 10).