Using R Programming for Somatoploting
Published 30-04-2024
Keywords
- R programming,
- RStudio,
- Somatotyping,
- Somatochart,
- Somatotypes
How to Cite
Copyright (c) 2024 Dattaniranjan Nandikolmath, Rupesh Samanchi, Barsha Rana, Aruna Hallikeri
This work is licensed under a Creative Commons Attribution 4.0 International License.
Dimensions
Abstract
Introduction: Anthropometry is a technique employed to evaluate body dimensions and ratios by examining body length, width, circumference, and skinfold thickness. It is cost-effective, uncomplicated, and easily transportable, and it may be used in diverse industries. Somatotyping is a primary method used to classify the human physique based on three main components: endomorphy, mesomorphy, and ectomorphy. Heath and Carter established and modified the standards of somatotype, which continue to be employed for global measurements. Several software tools have been created for somatoploting, including SAS/GRAPH, Houcine, Orhan, and machine-learning models. Nevertheless, most of these tools are not open-source, resulting in laborious manual enumeration and hindering the accurate representation of differences among groups. A functional, open-source, precise tool is required to categorise somatotypes of extensive sample sizes and illustrate their differences. Method: R programming is a powerful and versatile programme language, particularly popular in statistical computing and graphics. It is widely used in various fields, like biostatistics, bioinformatics, and financial market analysis. R incorporates original programming concepts like object-oriented programming, which users can use transparently. This paper introduces how to use R programming as a tool for somatoploting, introduces the code for somatoploting, inserts x and y data, and executes the program to get a somatochart. It uses anthropometric data of 34 school-going students collected in Shindikurbet, Karnataka, aged between 10 and 12 years, collected through ISAK protocol guidelines to develop somatotypes and further plot them. Result: The paper holistically demonstrates using R programming to plot somatotypes in a 2-D Somatochart. Using this process, the reader can develop high-quality somatocharts in image or PDF formats. Conclusion: This study explores using R programming, an open-source software, for somatoploting and generating somatocharts. This method aids in understanding complex information, fact-explaining, and guiding action in various fields. It offers accessible data processing, analysis, and presentation, making implementing and saving budgets for students, researchers, and institutions easy. Further research could be conducted to make the code easier to use in Excel sheets or mobile applications.
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