Non identified systematic errors in data sets can cause severe problems inducing wrong decisions in function control, process modelling or planning of new treatment infrastructure. In this paper statistical methods are shown to identify systematic errors in full-scale WWTP data sets. With a redundant mass balance approach analyzing five different mass balances, systematic errors of about 10%–20% compared to the input fluxes can be identified at a 5%-significance level. A Shewhart control-chart approach to survey the data quality of on-line-sensors allows a statistical as well as a fast graphical analysis of the measurement process. A 19 month data set indicates that NO3, PO4 and NH4 on-line analyzers in the filter effluent and MLSS sensors in the aeration tanks were not disturbed by any systematic error for 85–95% of the measuring time. The in-control-interval (±3·standard deviation) has a width of ±12–17% (NO3-N), ±35–40% (PO4-P), ±83% (NH4-N) and ±12–15% (TS) of the measured reference value.