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The sample mean or empirical mean and the sample covariance are statistics computed from a collection of data on one or more random variables. The sample mean is a vector each of whose elements is the sample mean of one of the random variablesthat is, each of whose elements is the arithmetic average of the observed values of one of the variables. The sample covariance matrix is a square matrix whose ''i, j'' element is the sample covariance (an estimate of the population covariance) between the sets of observed values of two of the variables and whose ''i, i'' element is the sample variance of the observed values of one of the variables. If only one variable has had values observed, then the sample mean is a single number (the arithmetic average of the observed values of that variable) and the sample covariance matrix is also simply a single value (the sample variance of the observed values of that variable). ==Sample mean== Let be the ''i''th independently drawn observation (''i=1,...,N'') on the ''j''th random variable (''j=1,...,K''). These observations can be arranged into ''N'' column vectors, each with ''K'' entries, with the ''K'' ×1 column vector giving the ''i''th observations of all variables being denoted (''i=1,...,N''). The sample mean vector is the average value of the ''N'' observations of the ''j''th variable: : Thus, the sample mean vector contains the average of the observations for each variable, and is written : 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「Sample mean and covariance」の詳細全文を読む スポンサード リンク
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