Abstract
Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.
Keywords
CausationCounterfactual thinkingPearlCausality (physics)Counterfactual conditionalExposition (narrative)Field (mathematics)EpistemologyVariety (cybernetics)Probabilistic logicCausal reasoningComputer scienceCognitionManagement sciencePsychologyData scienceCognitive scienceArtificial intelligencePhilosophyMathematicsEngineering
Affiliated Institutions
Related Publications
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of ...
Reflecting on reflexive thematic analysis
Since initially writing on thematic analysis in 2006, the popularity of the method we outlined has exploded, the variety of TA approaches have expanded, and, not least, our thin...
Mendelian randomization as an instrumental variable approach to causal inference
In epidemiological research, the causal effect of a modifiable phenotype or exposure on a disease is often of public health interest. Randomized controlled trials to investigate...
A Bayesian Morphometry Algorithm
Most methods for structure-function analysis of the brain in medical images are usually based on voxel-wise statistical tests performed on registered magnetic resonance (MR) ima...
Comparison of multiple Amber force fields and development of improved protein backbone parameters
Abstract The ff94 force field that is commonly associated with the Amber simulation package is one of the most widely used parameter sets for biomolecular simulation. After a de...
Publication Info
- Year
- 2009
- Type
- book
- Citations
- 10427
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
10427
OpenAlex
Cite This
Judea Pearl
(2009).
Causality.
Cambridge University Press eBooks
.
https://doi.org/10.1017/cbo9780511803161
Identifiers
- DOI
- 10.1017/cbo9780511803161