A practical methodology for the systematic identification of outliers

Accurate reporting of results is extremely important. This is especially relevant for energy and environmental data associated with government driven incentives and disincentives (such as tax benefits for energy efficiency or mandatory GHG emission reporting). Any abnormalities in the data can significantly affect reported results. It is therefore critically important to properly evaluate all data in a manner that is compliant with the relevant legislative requirements. Failure to do this can have financial and legal repercussions. There are several existing statistical methods to identify potential abnormalities or outliers in data. However, the practical application of these abstract methods can be challenging. This paper introduces the reader to some basic statistics concepts and formulas. These are used to construct a practical methodology combining simple formulas and visual representation of data to simplify the evaluation process. The developed methodology is systematically applied to a case study and the final result compared to the output of an industry accepted statistical approach. The results illustrate that a simple structured intuitive process can deliver similar results than a complex and abstract statistical approach.