Editing Indeterminism (section)

==Probabilistic causation==

{{main|Probabilistic causation}}

Interpreting [[causality|causation]] as a [[Causal determinism|deterministic]] relation means that if ''A'' causes ''B'', then ''A'' must always be followed by ''B''. In this sense, however, war does not always cause deaths (see [[Cyberwarfare]]), nor does a singular moment of [[Tobacco smoking|smoking]] always cause [[cancer]]. As a result, many turn to a notion of [[probabilistic causation]].  Informally, ''A'' '''probabilistically''' causes ''B'' if ''A''<nowiki>'</nowiki>s occurrence increases the probability of ''B''.  This is sometimes interpreted to reflect the imperfect knowledge of a deterministic system  but other times interpreted to mean that the causal system under study has an inherently indeterministic nature. ([[Propensity probability]] is an analogous idea, according to which probabilities have an objective existence and are not just limitations in a subject's knowledge).<ref>[http://plato.stanford.edu/entries/probability-interpret/ Stanford Encyclopedia of Philosophy: ''Interpretations of Philosophy'']</ref>

It can be proved that realizations of any [[probability distribution]] other than the [[uniform distribution (continuous)|uniform]] one are mathematically equal to applying a (deterministic) function (namely, an [[inverse distribution function]]) on a random variable following the latter (i.e. an "absolutely random" one<ref>The uniform distribution is the most "agnostic" distribution, representing lack of any information. [[Laplace]] in his theory of probability was apparently the first one to notice this. Currently, it can be shown using definitions of [[Entropy (information theory)|entropy]].</ref>); the probabilities are contained in the deterministic element. A simple form of demonstrating it would be shooting randomly within a square and then (deterministically) interpreting a relatively large subsquare as the more probable outcome.