Judea Pearl: Causal

Judea Pearl is Computer scientist. Explore interesting quotes on causal.

Judea Pearl: 18 quotes0 likes

“The research questions that motivate most quantitative studies in the health, social and behavioral sciences are not statistical but causal in nature. For example, what is the efficacy of a given drug in a given population? Whether data can prove an employer guilty of hiring discrimination? What fraction of past crimes could have been avoided by a given policy? What was the cause of death of a given individual, in a specific incident? These are causal questions because they require some knowledge of the data-generating process; they cannot be computed from the data alone.”

Pearl, Judea (2008) "Causal Inference," in: Pearl, Judea. The science and ethics of causal modeling. (2010).

“Bayesian networks [is] a term coined in Pearl (1985) to emphasize three aspects: (1) the subjective nature of the input information; (2) the reliance on Bayes' conditioning as the basis of updating information; (3) the distinction between causal and evidential models of reasoning, a distinction that underscores Thomas Bayes' paper of 1763”

Source: Causality: Models, Reasoning, and Inference, 2000, p. 14

“Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon.”

Pearl, Judea. "Causal inference in statistics: An overview." Statistics Surveys 3 (2009): 96-146.