www.gusucode.com > stats 源码程序 matlab案例代码 > stats/MeasuresOfCentralTendencyExample.m
%% Measures of Central Tendency % This example shows how to compute and compare measures of location for % sample data that contains one oulier. % Copyright 2015 The MathWorks, Inc. %% % Generate sample data that contains one outlier. x = [ones(1,6),100] %% % Compute the geometric mean, harmonic mean, mean, median, and trimmed mean % for the sample data. locate = [geomean(x) harmmean(x) mean(x) median(x)... trimmean(x,25)] %% % The mean (|mean|) is far from any data value because of % the influence of the outlier. The geometric mean (|geomean|) and the % harmonic mean (|harmmean|) are influenced by the outlier, but not as % significantly. The median (|median|) and trimmed mean (|trimmean|) % ignore the outlier value and describe the location of the rest of the % data values.