Causality is the relationship of cause and effect. the chain of causality that produces an earthquake. the relationship between a cause and the effect that it has
Can be linear and mono-directional (as in cause-effect); or circular (as in a closed sequence of cause-effect factors: cause-effect/cause-effect/cause-etc ) Example: one can observe that clouds cause rain; one can also observe that rain leads to evaporation, which give rise to clouds, which lead to rain, etc ; the difference is one of perspective and the observer's choice of boundaries
The relationship between cause and its effect It is a practical application of the law of non-contradiction
The relating of factors to the effects they produce Hill (a clinical epidemiologist) proposed eight criteria (not all essential) of a causal association between a factor and an outcome (see reference 9, page 77)
The relating of causes to the effects they produce Most of epidemiology concerns causality and several types of causes can be distinguished It must be emphasized, however, that epidemiological evidence by itself is insufficient to establish causality, although it can provide powerful circumstantial evidence
Anyone removed from active combat duty Includes those killed, wounded or otherwise unfit to return to combat duty This figure does not include those taken captive
Relating causes to the effects they produce Most of epidemiology concerns causality, and several types of causes can be distinguished A cause is termed "necessary" when a particular variable must always precede an effect This effect need not be the sole result of the one variable A cause is termed "sufficient" when a particular variable inevitably initiates or produces an effect Any given cause may be necessary, sufficient, neither, or both
Genus: Relationship Differentia: Describes how all causes have specific effects / all actions have specific reactions according to the nature of the entities involved Comment: This is the law of identity applied over time
A cause and effect relationship The causality of two events describes to what extent one event is caused by the other When there is causality, there is a measure of predictability between the two events
Given an event X in a physical system or a corresponding feature in a partial differential equation, a trichotomy which divides other events into those that may have caused or modified X, those which X can cause or alter, and those which are causally independent from X