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The word "cause" (or "causation") has multiple meanings in English. In philosophical terminology, "cause" can refer to necessary, sufficient, or contributing causes. In examining correlation, "cause" is most often used to mean "one contributing cause" (but not necessarily the only contributing cause).
The presence of x, however, does not imply that y will occur. [20] Sufficient causes If x is a sufficient cause of y, then the presence of x necessarily implies the subsequent occurrence of y. However, another cause z may alternatively cause y. Thus the presence of y does not imply the prior occurrence of x. [20] Contributory causes
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.
In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation).
Here is the example the two events may coincide or correlate, but have no causal connection. [2] Fallacies of questionable cause include: Circular cause and consequence [citation needed] Correlation implies causation (cum hoc, ergo propter hoc) Third-cause fallacy; Wrong direction; Fallacy of the single cause; Post hoc ergo propter hoc
If the U.S. Congress passes a bill, the president's signing of the bill is sufficient to make it law. Note that the case whereby the president did not sign the bill, e.g. through exercising a presidential veto, does not mean that the bill has not become a law (for example, it could still have become a law through a congressional override ...
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 ...
Causal inference – Branch of statistics concerned with inferring causal relationships between variables; Coincidence – Concurrence of events with no connection; Confirmation bias – Bias confirming existing attitudes; Correlation does not imply causation – Refutation of a logical fallacy; Jumping to conclusions – Psychological term