Causation is a study of the factors involved in causing something. Relation that holds between two temporally simultaneous or successive events when the first event (the cause) brings about the other (the effect). According to David Hume, when we say of two types of object or event that "X causes Y" (e.g., fire causes smoke), we mean that (i) Xs are "constantly conjoined" with Ys, (ii) Ys follow Xs and not vice versa, and (iii) there is a "necessary connection" between Xs and Ys such that whenever an X occurs, a Y must follow. Unlike the ideas of contiguity and succession, however, the idea of necessary connection is subjective, in the sense that it derives from the act of contemplating objects or events that we have experienced as being constantly conjoined and succeeding one another in a certain order, rather than from any observable properties in the objects or events themselves. This idea is the basis of the classic problem of induction, which Hume formulated. Hume's definition of causation is an example of a "regularity" analysis. Other types of analysis include counterfactual analysis, manipulation analysis, and probabilistic analysis
The rule particularly in criminal law that the defendant has to have caused the result or consequence The causation can be either in law or fact So, death is the result or consequence of murder and has to be strictly proved by the prosecution Often the 'but for test' is applied, 'but for what the defendant did would the result have occurred?'
In causal relations between events, if an event of the first kind occurs, an event of the second kind will or must occur, and the first event will explain the occurence of the second event Possibly items other that events can enter into causal relations Since Hume, we have been puzzled about whether causal relations are real or are just matters of our imposing our habits upon the world and over the nature of causal necessity
A relationship between bivariate variables X and Y that holds when it is known that varying X causes a change in the value of Y; a correlation, even when large, between X and Y does not imply causation
the relationship that results when a change in one variable is not only correlated with but actually causes a change in another variable; the change in the second variable is a consequence of the change in the first variable, rather than both changes being a consequence of a change in a third variable
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