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The phrase " correlation does not imply causation " refers to the inability to legitimately deduce a cause-and-effect relationship between two events or variables solely on the basis of an observed association or correlation between them. [1][2] The idea that "correlation implies causation" is an example of a questionable-cause logical fallacy ...
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.
Relief theory suggests humor is a mechanism for pent-up emotions or tension through emotional relief. In this theory, laughter serves as a homeostatic mechanism by which psychological stress is reduced [1] [2] [6] Humor may thus facilitate ease of the tension caused by one's fears, for example.
Bradford Hill criteria. The Bradford Hill criteria, otherwise known as Hill's criteria for causation, are a group of nine principles that can be useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an observed effect and have been widely used in public health research.
Causality. Causality is an influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. In general, a process can have multiple causes ...
Clip of woman laughing. Laughter is a pleasant physical reaction and emotion consisting usually of rhythmical, often audible contractions of the diaphragm and other parts of the respiratory system. It is a response to certain external or internal stimuli. Laughter can rise from such activities as being tickled, [ 1 ] or from humorous stories ...
Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, [1][2][3] and is particularly problematic when frequency data are unduly given causal ...
Sample Ishikawa diagram shows the causes contributing to problem. The defect, or the problem to be solved, [1] is shown as the fish's head, facing to the right, with the causes extending to the left as fishbones; the ribs branch off the backbone for major causes, with sub-branches for root-causes, to as many levels as required.