Year: 2017
Type: article
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.
Source: 대한치과의사협회지
Author: Ki-Yeol Kim
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4401523430