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  2. File:Venn diagram.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Venn_diagram.pdf

    English: Venn diagram picturing relationships between elements within self-determination theory of student motivation. As per this is the uploader's own work as the diagram has been developed from the referenced source to to illustrate the three important elements discussed in the article. This image should be corrected to read "based on ...

  3. 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.

  4. Set theory - Wikipedia

    en.wikipedia.org/wiki/Set_theory

    Set theory is the branch of mathematical logic that studies sets, which can be informally described as collections of objects.Although objects of any kind can be collected into a set, set theory – as a branch of mathematics – is mostly concerned with those that are relevant to mathematics as a whole.

  5. File:Couturat 1914 p 74 example Venn minterms.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Couturat_1914_p_74...

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  6. Square of opposition - Wikipedia

    en.wikipedia.org/wiki/Square_of_opposition

    Square of opposition. The lower case letters (a, e, i, o) are used instead of the upper case letters (A, E, I, O) here in order to be visually distinguished from the surrounding upper case letters S (Subject term) and P (Predicate term). In the Venn diagrams, black areas are empty and red areas are nonempty. White areas may or may not be empty.

  7. Information diagram - Wikipedia

    en.wikipedia.org/wiki/Information_diagram

    Information diagrams have also been applied to specific problems such as for displaying the information theoretic similarity between sets of ontological terms. [ 3 ] Venn diagram showing additive and subtractive relationships among various information measures associated with correlated variables X and Y .