**12. Conclusions**

A new method for detecting outliers was proposed in this paper. The method is applicable to any continuous distribution at any risk being in error. It was proved that the method correctly detects the outliers. For a normal distribution at 5% risk being in error, it was also shown that the proposed method outperforms the classical Grubbs test for detecting the outliers.

**SupplementaryMaterials:**Details of the software used for deriving the results givenin the figures and tables, algorithms and source codes are given as supplementary material available online at http://www.mdpi.com/2073-8994/11/6/835/s1.

**Funding:** This research received no external funding.

**Acknowledgments:** Thanks to my colleague S.D. Bolboacă and for our fruitful discussions during the development stage of the study, which helped and motivated the author to complete the study.

**Conflicts of Interest:** The author declares no conflict of interest.
