Choosing the appropriate measure of central tendency: mean, median, or mode?

Abstract

Mean, median, and mode are among the most basic and consistently used measures of central tendency in statistical analysis and are crucial for simplifying data sets to a single value. However, there is a lack of understanding of when to use each metric and how various factors can impact these values. The aim of this article is to clarify some of the confusion related to each measure and explain how to select the appropriate metric for a given data set. The authors present this work as an educational resource, ensuring that these common statistical concepts are better understood throughout the Orthopedic research community.

The Impact of Various Cockpit Display Interfaces on Novice Pilots’ Mental Workload and Situational Awareness: A Comparative Study

“…Therefore, the Wilcoxon test was used to examine the impact of the type of CDI (two levels) on the dependent variables, while the Friedman test was applied to address the influence of the difficulty of the N-back task (three levels) on the dependent variables [52]. Median rather than mean values were used in the data analysis because of the relatively small sample size and to reduce outlier effects [53].…”

Deep Reinforcement Learning for Workload Prediction in Federated Cloud Environments

“…If the mean is used, it would be significantly impacted by the outliers. Thus, median is robust as it less sensitive to extreme values in the context of CPU utilization [ 45 ]. With the violin plot, the central tendency of CPU utilization across different model workloads is illustrated while considering the spread and shape of the distributions.…”

The only constant in life is change: A moment of gratitude and respect for the past and a start for the new KSSTA team!

“…Under his guidance, KSSTA has tremendously grown in both the quantity and quality of submissions and publications, solidifying its position among the top 10 journals in the field of orthopaedics and sports traumatology. Jon Karlsson has always embraced and introduced new ways of disseminating the voice of KSSTA in the scientific community [1,5,8,[12][13][14], alongside leading numerous educational initiatives aimed at teaching younger, less skilled researchers with the basic publishing skills set needed [2,4,6,7,[9][10][11]. In addition, he has built a fantastic team of editors and associate editors for whom he served as a role model.…”