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In mathematics, mean has several different definitions depending on the context. In probability and statistics, mean and expected value are used synonymously to refer to one measure of the central tendency either of a probability distribution or of the random variable characterized by that distribution. In the case of a discrete probability distribution of a random variable ''X'', the mean is equal to the sum over every possible value weighted by the probability of that value; that is, it is computed by taking the product of each possible value ''x'' of ''X'' and its probability P(''x''), and then adding all these products together, giving .〔Elementary Statistics by Robert R. Johnson and Patricia J. Kuby, (p. 279 )〕 An analogous formula applies to the case of a continuous probability distribution. Not every probability distribution has a defined mean; see the Cauchy distribution for an example. Moreover, for some distributions the mean is infinite: for example, when the probability of the value is for n = 1, 2, 3, .... For a data set, the terms arithmetic mean, mathematical expectation, and sometimes average are used synonymously to refer to a central value of a discrete set of numbers: specifically, the sum of the values divided by the number of values. The arithmetic mean of a set of numbers ''x''1, ''x''2, ..., ''xn'' is typically denoted by , pronounced "''x'' bar". If the data set were based on a series of observations obtained by sampling from a statistical population, the arithmetic mean is termed the sample mean (denoted ) to distinguish it from the population mean (denoted or ).〔Underhill, L.G.; Bradfield d. (1998) ''Introstat'', Juta and Company Ltd. ISBN 0-7021-3838-X (p. 181 )〕 For a finite population, the population mean of a property is equal to the arithmetic mean of the given property while considering every member of the population. For example, the population mean height is equal to the sum of the heights of every individual divided by the total number of individuals. The sample mean may differ from the population mean, especially for small samples. The law of large numbers dictates that the larger the size of the sample, the more likely it is that the sample mean will be close to the population mean.〔Schaum's Outline of Theory and Problems of Probability by Seymour Lipschutz and Marc Lipson, (p. 141 )〕 Outside of probability and statistics, a wide range of other notions of "mean" are often used in geometry and analysis; examples are given below. ==Types of mean== 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「Mean」の詳細全文を読む スポンサード リンク
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