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Cause, Effect, and Everything in Between
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Abstract
The book offers a concise and accessible introduction to causal inference, employing a non-technical approach. It focuses on developing the reader’s ability to analyze and critique research studies through a causal perspective. It starts by defining causal questions, causes, and effects. It then explores different types of causal inference problems, graphical tools for expressing causality, the shortcomings of randomized trials, and methods for inferring causality from observational data. The book covers many examples and case studies with answers. The book is mainly written for those who may have trouble interpreting and assessing causal claims in their everyday life, such as people who like to keep up with the news, but also professionals like journalists and policymakers who need to make sense of academic research. Another intended audience is non-STEM college students who usually do not take any courses on the subject.
Title: Cause, Effect, and Everything in Between
Description:
Abstract
The book offers a concise and accessible introduction to causal inference, employing a non-technical approach.
It focuses on developing the reader’s ability to analyze and critique research studies through a causal perspective.
It starts by defining causal questions, causes, and effects.
It then explores different types of causal inference problems, graphical tools for expressing causality, the shortcomings of randomized trials, and methods for inferring causality from observational data.
The book covers many examples and case studies with answers.
The book is mainly written for those who may have trouble interpreting and assessing causal claims in their everyday life, such as people who like to keep up with the news, but also professionals like journalists and policymakers who need to make sense of academic research.
Another intended audience is non-STEM college students who usually do not take any courses on the subject.
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