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  2. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    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.

  3. Prediction in language comprehension - Wikipedia

    en.wikipedia.org/wiki/Prediction_in_language...

    The PARLO ("Production Affects Reception in Left Only") framework is a theory of the neural domains supporting language prediction. It is based on evidence that shows that the left and right hemispheres differentially contribute to language comprehension. [ 17 ]

  4. Causality (book) - Wikipedia

    en.wikipedia.org/wiki/Causality_(book)

    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]

  5. Causal reasoning - Wikipedia

    en.wikipedia.org/wiki/Causal_reasoning

    Causal reasoning is the process of identifying causality: the relationship between a cause and its effect.The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one.

  6. Exploratory causal analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_causal_analysis

    Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. [1] [2] Exploratory causal analysis (ECA), also known as data causality or causal discovery [3] is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions.

  7. Causal analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_analysis

    Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...

  8. Theory of language - Wikipedia

    en.wikipedia.org/wiki/Theory_of_language

    Theory of language is a topic in philosophy of language and theoretical linguistics. [1] It has the goal of answering the questions "What is language?"; [2] [3] "Why do languages have the properties they do?"; [4] or "What is the origin of language?". In addition to these fundamental questions, the theory of language also seeks to understand ...

  9. Causal AI - Wikipedia

    en.wikipedia.org/wiki/Causal_AI

    Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for causal AI is for organisations to explain decision-making and the causes for a decision.