OUTLIER=GROSS ERROR? DO ONLY GROSS ERRORS CAUSE OUTLIERS IN GEODETIC NETWORKS? ADDRESSING THESE AND OTHER QUESTIONS

Abstract This article has theoretically discussed some points regarding outliers caused by errors in geodetic observations (see consideration made). Comments have also been made on the usual 3σ-rule to identify outliers and its common approachs in the simulation of outliers in geodetic networks. Three simulated experiments have been conducted to verify the elements discussed. In the first one, with the simulation of random errors, we have verified that it can have a magnitude large enough to generate outliers. In the second one, in scenarios of leveling network simulated by Monte Carlo methods, observations containing gross errors with a lower magnitude than their respective σ tended to not be identified as outliers by the iterative data snooping procedure. This has also occurred in the third experiment, in which gross errors of magnitude 3.1σ had their value masked by the random error of the respective observation. From the conceptual discussion presented, we have concluded that gross error and outlier are not synonyms, and neither is one a particular case of the other. From the obtained results, we have concluded that there are inconsistencies in how outliers have been simulated in geodetic networks, which indicates the need to continue with investigations.