Related Experiment Video
Updated: Oct 30, 2025

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
Published on: June 20, 2020
Analysis of Children's Physical Characteristics Based on Clustering Analysis
Eunjung Kim1, Yumi Won2, Jieun Shin3
1Division of Sports Science, Myongji University, Yongin-si 17058, Korea.
Abstract:
This study assessed the physical development, physical fitness (muscular endurance, muscular strength, flexibility, agility, power, balance), and basal metabolic rate (BMR) in a total of 4410 children aged six (73-84 months) residing in Korea. Their physical fitness was visually classified according to the physical fitness factor and-considering that children showed great variations in the physical fitness criteria depending on their physique and body composition-the study aimed to assess characteristics such as physique and BMR, the precursor for fat-free mass, based on the physical health clusters selected through a multivariate approach. As a result, the physical health clusters could be subdivided into four clusters: balance (1), muscular strength (2), low agility (3), and low physical fitness (3) cluster. Cluster 1 showed a high ratio of slim and slightly slim children, while cluster 2 had a high proportion of children that were obese, tall, or heavy, and had the highest BMR. We consider such results as important primary data for constituting physical fitness management programs customized to each cluster. It seems that it is necessary to have a multidirectional approach toward physical fitness evaluation and analysis methodologies that involve various physical fitness factors of children.
More Related Videos
Related Concept Videos
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Pedigree Analysis
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Karyotyping
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Variation: Normal Distribution, Range, and Standard Deviation

