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在处理一列测量数据时,如果其中有粗差未予剔除或将一些误差较大而不属粗差的观测值剔除,都会歪曲了测量结果,所以首先需要判别测量列中是否包含有粗差的观测值。供判别粗差的一些熟知法则有:莱依达法则、肖维勒法则和文中给出的较好 t 判别法,本文再介绍一个简便的判别法——狄克逊法则,然后再谈如何用极差计算随机不确定度的方法。一、剔除坏值对某一个量同一条件下,独立测得 n 个值:
When dealing with a series of measurement data, if there is a gross error unrecorded, or some of the errors are not gross errors removed, will distort the measurement results, it is first necessary to determine whether the measured column contains a gross error Observations. Some of the well-known rules for judging gross errors are: Leida, Chowler’s law and the better t discriminant given in this paper. This article will then introduce a simple discriminant-the Dixon rule-and then talk about how to use Method of Calculating Stochastic Uncertainty. First, remove the bad value of a certain amount of the same conditions, the independent measured n values: