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Hello! I am a bit confused about estimating the systematic error (I think it is systematic) from an experiment. Here is a (simplified) description of it. Assume that 2 groups measure the length of a cube with 2 different rulers, which, due to some effects give slightly different results (for example they are made of different materials and they have different lengths due to thermal expansion). Assume that they associate the same error ##dx## to each of their measurement (based on the grading of the ruler) and for each group the same number of measurements is made. After a big number of measurements the data is presented in a histogram and 2 peaks appear, with a similar standard deviation (although this is not that important) but 2 clearly separated means ##\mu_1## and ##\mu_2##. Obviously one of the measurements is not right (or maybe both), so I think that this difference can be considered a systematic error. Now, if I had just one peak, the average length would be the mean of the gaussian peak and the error would be ##\sigma/\sqrt{N}##, where N is the number of measurements and ##\sigma## their standard deviation. However, now I need to take into account the fact that I don't know which one of the 2 peaks is right so I need to attach an error associated to that, too. How should I do it properly? Thank you!