Statistical methods for QA/QC of analytical data exemplified by IAEA programmes on airborne particulate matter

An introduction to data validation methods is presented with examples. Data validation is the process of examining the results of the analytical methodology to identify potential problems within the analytical process, unusual events during the sampling period, or errors in transcribing and presenting the results. The use of such processes means that only validated data are employed for further analyses, and can thus be better relied upon as a basis for decision making because of the reliability of the information. Examples of data validation are given using results from the IAEA's two Co-ordinated Research Programmes on the application of nuclear analytical techniques for the analysis of airborne particulate matter. (author)