Article ID: | iaor201110327 |
Volume: | 61 |
Issue: | 4 |
Start Page Number: | 1240 |
End Page Number: | 1244 |
Publication Date: | Nov 2011 |
Journal: | Computers & Industrial Engineering |
Authors: | Drezner Zvi, Turel Ofir |
Keywords: | gaussian processes |
Many quantitative applications in business operations, environmental engineering, and production assume sufficient normality of data, which is often, demonstrated using tests of normality, such as the Kolmogorov deemed Smirnov test. A practical problem arises when a high proportion of a too‐frequent value exists in data, in which case transformation to normality that passes tests for normality may be impossible. Analysts and researchers are therefore often concerned with the question: should we bother transforming the variable to normality? Or should we revert to other approaches not requiring a normal distribution? In this study, we find the critical number of the frequency of a single value for which there is no feasible transformation to normality within a given