An improved method for eliminating the outlier values in small sample

Abstract

Under the condition of the small sample [1,2,3,4,5] , it is no longer possible to simply use the mean and variance of all the data to remove outlier values. Method of hampel is simple and rough in small sample, it will be greatly affected by the outlier value that once enters the middle 50% of all the data. Method of boxplot [6,7,8] will cause the interquartile range (IQR) to be too large and make the outlier value become normal. In order to solve the above problems, this paper improves the method of boxplot by using the median to eliminate the outlier value in the middle 50% of all the data. Then we use the remaining data to calculate the mean value and variance. At last by use of the 3 principles of method of hampel, we eliminate the outlier values and obtain the true and non-outlier values. The effect of the algorithm of this paper is useful and ideal by data simulation. It can be applied to engineering practice.