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In statistics, consistency of procedures, such as computing confidence intervals or conducting hypothesis tests, is a desired property of their behaviour as the number of items in the data set to which they are applied increases indefinitely. In particular, consistency requires that the outcome of the procedure with unlimited data should identify the underlying truth.〔Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. ISBN 0-19-920613-9 (entries for consistency, consistent estimator, consistent test)〕 Use of the term in statistics derives from Sir Ronald Fisher in 1922.〔Upton, G.; Cook, I. (2006) ''Oxford Dictionary of Statistics'', 2nd Edition, OUP. ISBN 978-0-19-954145-4〕 Use of the terms ''consistency'' and ''consistent'' in statistics is restricted to cases where essentially the same procedure can be applied to any number of data items. In complicated applications of statistics, there may be several ways in which the number of data items may grow. For example, records for rainfall within an area might increase in three ways: records for additional time periods; records for additional sites with a fixed area; records for extra sites obtained by extending the size of the area. In such cases, the property of consistency may be limited to one or more of the possible ways a sample size can grow. ==Estimators== (詳細はconsistent estimator is one for which, when the estimate is considered as a random variable indexed by the number ''n'' of items in the data set, as ''n'' increases the estimates converge to the value that the estimator is designed to estimate. (詳細はFisher consistency is one for which, if the estimator were applied to the entire population rather than a sample, the true value of the estimated parameter would be obtained. 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「Consistency (statistics)」の詳細全文を読む スポンサード リンク
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