Scientific metrics on bibliometric studies: detection of outliers for univariate data
DOI:
https://doi.org/10.19132/1808-5245230.254-273Keywords:
Outliers. Exploratory Data Analysis. Asymmetry. Bibliometry. Univariate.Abstract
This study presents formulas for detection of outliers for univariate data, taking into consideration the positive as well as the negative asymmetry of data. This new formula is based on the Exploratory Data Analysis and is simulated through the comparison of the outcome of the Exploratory Data Analysis found in statistical text books and statistical software. However, only normal or Gaussian distribution, i.e., symmetric or slightly asymmetric values, are applied. Real data published in two scientific papers on metrics are used for the simulation. For moderate or strong positive (negative) asymmetries, the new formulation detects a lower (higher) quantity of superior outliers. It is important to take into account the existence of outliers in bibliometric data; it is recommended to quantify the influence of outliers in statistical calculation, such as mean and standard deviation.Downloads
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