SUMMARY

Most of the surveying tasks involve the acquisition and analysis of measurements.Such measurements are subject to random, systematic and gross errors. In practice, redundantmeasurements are made to provide quality control and errors check. In qualitative analysisand statistical evaluation, it is generally assumed that the measurements contain only randomerrors and are regarded as random variables. In reality, the measurements may contain grossand/or systematic errors. The effects of such errors are distributed over the residuals, after anadjustment and lead to questionable results and interpretation.For high precision applications, gross and systematic errors need to be detected prior to theanalysis. These errors should be tackled before the adjustment by means of screening. Thesefew remaining gross errors in the measurements can be detected after the adjustment. Theseadjustment methods assume the presence of only one gross error. One of the most effectivemethods that can be used in detecting multiple gross errors is the statistical quality controlmethod. Statistical quality control is a technique used to monitor a procedure with a goal ofmaking it more efficient and ensures precise results.Statistical control charts are used to provide an operational definition of a special cause for agiven set of data. It is possible to construct multiples of sigma control limits. When all thepoints on a control chart are within a multiple of sigma control limits and there are no grosserrors in the data, the process of measurements is said to be in a state of statistical control.Otherwise, the data indicate the presence of non-random gross errors. In this research work,different methods of statistical quality control were used. Results showed that statisticalquality control method can be used successfully and efficiently in detecting multiple grosserrors.