Causal inference is perhaps the most important form of reasoning in
the sciences. A panoply of disciplines, ranging from epidemiology
to biology, from econometrics to physics, make use of probability
and statistics in order to infer causal relationships. However, the
very foundations of causal inference are up in the air; it is by no
means clear which methods of causal inference should be used, nor
why they work when they do. This book brings philosophers and
scientists together to tackle these important questions. The papers
in this volume shed light on the relationship between causality and
probability and the application of these concepts within the
sciences. With its interdisciplinary perspective and its careful
analysis, "Causality and Probability in the Sciences" heralds the
transition of causal inference from an art to a science.
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