数据的统计说明.第8部分:预测差异的测定

[中文适用范围]： ISO 16269 的这一部分指定了确定单个连续分布变量的预测区间的方法。 这些是从大小为 n 的随机样本导出的变量值的范围，对于这些变量值的范围，可以以指定的置信度进行与来自同一总体的大小为 m 的进一步随机选择的样本相关的预测。 考虑三种不同类型的总体，即： a) 标准差未知的正态分布； b) 具有已知标准差的正态分布； c) 连续但形式未知。 对于这三种类型的总体中的每一种，提出了两种方法，一种用于单侧预测区间，一种用于对称两侧预测区间。 在所有情况下，都可以从六个置信水平中进行选择。 针对情况 a) 和 b) 提出的方法也可用于可转换为正态分布的非正态分布总体。 对于情况 a) 和 b)，ISO 16269 本部分中提供的表格仅限于包含变量的所有其他 m 个采样值的预测区间。 对于情况 c)，这些表涉及至少包含接下来 m 个值中的 m – r 个值的预测区间，其中 r 取 0 到 10 或 0 到 m – 1 之间的值，以范围较小者为准。 对于正态分布的总体，还提供了计算 m 个进一步观察平均值的预测区间的过程。 [外文原描述]： ISO 16269-8:2004 specifies methods of determining prediction intervals for a single continuously distributed variable. These are ranges of values of the variable, derived from a random sample of size n , for which a prediction relating to a further randomly selected sample of size m from the same population may be made with a specified confidence . Three different types of population are considered, namely normally distributed with unknown standard deviation, normally distributed with known standard deviation, and continuous but of unknown form. For each of these three types of population, two methods are presented, one for one-sided prediction intervals and one for symmetric two-sided prediction intervals. In all cases, there is a choice from among six confidence levels. The methods presented for types of population that are normally distributed with unknown standard deviation and normally distributed with known standard deviation may also be used for non-normally distributed populations that can be transformed to normality. For types of population that are normally distributed with unknown standard deviation and normally distributed with known standard deviation, the tables presented in ISO 16269-8:2004 are restricted to prediction intervals containing all the further m sampled values of the variable. For types of population that are continuous but of unknown form, the tables relate to prediction intervals that contain at least m - r of the next m values, where r takes values from 0 to 10 or 0 to m - 1, whichever range is smaller. For normally distributed populations, a procedure is also provided for calculating prediction intervals for the mean of m further observations.