Outlier detection in dental research

치의학 연구에서 이상치의 처리

  • Kim, Ki-Yeol (BK21 PLUS Project, Dental Education Research Center, Yonsei University College of Dentistry)
  • 김기열 (연세대학교 치과대학 BK21 플러스 통합구강생명과학 사업단, 치의학 교육연구센터)
  • Received : 2017.05.11
  • Accepted : 2017.06.30
  • Published : 2017.09.30

Abstract

In clinical dental research, errors occur in spite of careful study design and conduct. Data cleaning procedures intend to identify and correct these errors or at least to minimize their influence on study. Outlier is the one of these errors. Outlier detection is the first step in data analysis process which has a serious effect in the field of dental research. Hence, this paper aims to introduce the methods to detect the outliers and to examine their influences in statistical data analysis.

Keywords

Acknowledgement

Supported by : 연세대학교 치과대학

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