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  2. Venn diagram - Wikipedia

    en.wikipedia.org/wiki/Venn_diagram

    A Venn diagram is a widely used diagram style that shows the logical relation between sets, popularized by John Venn (1834–1923) in the 1880s. The diagrams are used to teach elementary set theory, and to illustrate simple set relationships in probability, logic, statistics, linguistics and computer science.

  3. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    v. t. e. Data and information visualization (data viz/vis or info viz/vis) [ 2 ] is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount [ 3 ] of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items.

  4. Syllogism - Wikipedia

    en.wikipedia.org/wiki/Syllogism

    Syllogism. A syllogism (Greek: συλλογισμός, syllogismos, 'conclusion, inference') is a kind of logical argument that applies deductive reasoning to arrive at a conclusion based on two propositions that are asserted or assumed to be true. "Socrates" at the Louvre. In its earliest form (defined by Aristotle in his 350 BC book Prior ...

  5. John Venn - Wikipedia

    en.wikipedia.org/wiki/John_Venn

    John Venn. John Venn, FRS, [2][3] FSA [4] (4 August 1834 – 4 April 1923) was an English mathematician, logician and philosopher noted for introducing Venn diagrams, which are used in logic, set theory, probability, statistics, and computer science. In 1866, Venn published The Logic of Chance, a groundbreaking book which espoused the frequency ...

  6. Information diagram - Wikipedia

    en.wikipedia.org/wiki/Information_diagram

    An information diagram is a type of Venn diagram used in information theory to illustrate relationships among Shannon's basic measures of information: entropy, joint entropy, conditional entropy and mutual information. [1][2] Information diagrams are a useful pedagogical tool for teaching and learning about these basic measures of information.

  7. Collectively exhaustive events - Wikipedia

    en.wikipedia.org/wiki/Collectively_exhaustive_events

    The events 1 and 6 are mutually exclusive but not collectively exhaustive. The events "even" (2,4 or 6) and "not-6" (1,2,3,4, or 5) are also collectively exhaustive but not mutually exclusive. In some forms of mutual exclusion only one event can ever occur, whether collectively exhaustive or not.

  8. Brainly - Wikipedia

    en.wikipedia.org/wiki/Brainly

    Brainly is an education company based in Kraków, Poland, with headquarters in New York City.It is an AI-powered homework help platform targeting students and parents. As of November 2020, Brainly reported having 15 million daily active users, making it the world's most popular education app. [2] In 2024, FlexOS reported Brainly as the #1 Generative AI Tool in the education category and the #6 ...

  9. Conditional mutual information - Wikipedia

    en.wikipedia.org/wiki/Conditional_mutual_information

    The conditional mutual informations , and are represented by the yellow, cyan, and magenta regions, respectively. In probability theory, particularly information theory, the conditional mutual information[1][2] is, in its most basic form, the expected value of the mutual information of two random variables given the value of a third.