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In statistics, a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model. Likelihood functions play a key role in statistical inference, especially methods of estimating a parameter from a set of statistics. In informal contexts, "likelihood" is often used as a synonym for "probability." But in statistical usage, a distinction is made depending on the roles of the outcome or parameter. ''Probability'' is used when describing a function of the outcome given a fixed parameter value. For example, if a coin is flipped 10 times and it is a fair coin, what is the ''probability'' of it landing heads-up every time? ''Likelihood'' is used when describing a function of a parameter given an ''outcome.'' For example, if a coin is flipped 10 times and it has landed heads-up 10 times, what is the ''likelihood'' that the coin is fair? ==Definition== The ''likelihood'' of a set of parameter values, θ, given outcomes x, is equal to the ''probability'' of those observed outcomes given those parameter values, that is :. The likelihood function is defined differently for discrete and continuous probability distributions. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「likelihood function」の詳細全文を読む スポンサード リンク
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