Multiple testing in the world of business - when and how?. (27th March 2019) - Clements, Nicolle
Multiplicity of data and compounding errors is often overlooked in data analysis for applied business scenarios. Statistical theory around multiple testing provides a framework for describing appropriate error rates and offers methods to control them in order to protect against wrong conclusions. However, these multiple testing procedures are often misunderstood and underutilised in applied business problems. In this article, existing multiple testing methodologies are reviewed and summarised. Specific numeric examples are shown to illustrate the techniques and demonstrate the statistical power of each. Finally, three cases are given of business-related situations when multiple testing can be overlooked in data analysis.