A simulation approach to multivariate quality control
Proceedings of the 21st international conference on Computers and industrial engineering
Statistical inference by normal probability paper
Computers and Industrial Engineering
(Q,r,L) inventory model with defective items
Computers and Industrial Engineering
A multi-criterion evaluation approach to selection of the best statistical distribution
Computers and Industrial Engineering
Mis-specification analysis between normal and extreme value distributions for a screening experiment
Computers and Industrial Engineering
| Hi-index | 0.00 |
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 @a of the Kolmogorov-Smirnov test. The resultant decision table can guide the effort of analysts and researchers.