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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.
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.
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).
As an example, a ball moving through the air (a process) is contrasted with the motion of a shadow (a pseudo-process). The former is causal in nature while the latter is not. Salmon (1984) [41] claims that causal processes can be identified by their ability to transmit an alteration over space and time. An alteration of the ball (a mark by a ...
The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship. [1] Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).
Inferences are said to possess internal validity if a causal relationship between two variables is properly demonstrated. [1] [2] A valid causal inference may be made when three criteria are satisfied: the "cause" precedes the "effect" in time (temporal precedence), the "cause" and the "effect" tend to occur together (covariation), and
The association fallacy is a formal logical fallacy that asserts that properties of one thing must also be properties of another thing if both things belong to the same group. For example, a fallacious arguer may claim that "bears are animals, and bears are dangerous; therefore your dog, which is also an animal, must be dangerous."
The identification of intervening variables and further replications of studies can also strengthen claims of causal inference. [3] Different methodological approaches make tradeoffs between statistical rigor (the ability to confidently attribute change to one variable or cause), qualitative depth, and finances available for research.