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Binary opposition is the system of language and/or thought by which two theoretical opposites are strictly defined and set off against one another. [1] It is the contrast between two mutually exclusive terms, such as on and off, up and down, left and right. [2] Binary opposition is an important concept of structuralism, which sees such ...
Splitting, also called binary thinking, dichotomous thinking, black-and-white thinking, all-or-nothing thinking, or thinking in extremes, is the failure in a person's thinking to bring together the dichotomy of both perceived positive and negative qualities of something into a cohesive, realistic whole.
The relationship between opposites is known as opposition. A member of a pair of opposites can generally be determined by the question What is the opposite of X ? The term antonym (and the related antonymy) is commonly taken to be synonymous with opposite, but antonym also has other more restricted meanings.
In linguistics, a yes–no question, also known as a binary question, a polar question, or a general question, [1] or closed-ended question is a question whose expected answer is one of two choices, one that provides an affirmative answer to the question versus one that provides a negative answer to the question.
In set theory, a dichotomous relation R is such that either aRb, bRa, but not both. [1]A false dichotomy is an informal fallacy consisting of a supposed dichotomy which fails one or both of the conditions: it is not jointly exhaustive and/or not mutually exclusive.
Part of understanding fallacies involves going beyond logic to empirical psychology in order to explain why there is a tendency to commit or fall for the fallacy in question. [ 9 ] [ 1 ] In the case of the false dilemma , the tendency to simplify reality by ordering it through either-or-statements may play an important role.
Dichotomous thinking or binary thinking in statistics is the process of seeing a discontinuity in the possible values that a p-value can take during null hypothesis significance testing: it is either above the significance threshold (usually 0.05) or below. When applying dichotomous thinking, a first p-value of 0.0499 will be interpreted the ...
Diagram of a binary classifier separating a set of samples into positive and negative values. The elements in the green area on the right are those classified as positive matches for the tested condition, while those on the pink area on the left were classified as negative matches.