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标准分数 （Standard Score，又称 z-score，中文称为 Z-分数 或 标准分 或 标准计分[1]）在 统计学 中是一种 无因次值，就是一种纯数字标记，是借由从单一（原始）分数中减去 总体 的 平均值，再依照 总体 （母集合）的 标准差 分割成不同的差距，按照z值公式. 標準分數 （Standard Score，又稱 z-score，中文稱為 Z-分數 或 標準分 或 標準計分[1]）在 統計學 中是一種 無因次值，就是一種純數字標記，是藉由從單一（原始）分數中減去 母體 的 平均值，再依照 母體 （母集合）的 標準差 分割成不同的差距，按照z值公式. Z-Score（标准分数）是衡量数据点相对于总体均值的位置，表示样本值与均值的差距以标准差为单位。 公式包括单个样本情况下的z=x−μσ和样本均值的标准误差z=x‾−μσ/n。 正负值分别表示高于或低于均值，其绝对值越大，表示偏离程度越高。
如上图所示，Z-Score的主要目的就是将不同量级的数据统一转化为同一个量级，统一用计算出的Z-Score值衡量，以保证数据之间的可比性。 In words, subtract the mean from the raw score and then divide by the standard deviation. z分数（z-score），也叫标准分数（standard score）是一个数与平均数的差再除以标准差的过程。 在统计学中，标准分数是一个观测或数据点的值高于被观测值或测量值的平均值的标准偏差的符号数。
Z 分数，也称为标准分数，是一种统计指标，用于衡量某个数据点与总体平均值之间的差距，用“标准差”为单位表示。 简单来说，Z 分数告诉我们一个数据点偏离平均值有多少个标准差。
More technically, it’s a measure of how many standard deviations below or above the population mean a raw score is. 一、Z-score介绍 Z-score是统计学中用于标准化数据的一种方法，它衡量一个数据点与数据集均值的偏差程度，以标准差为单位表示。
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