Article Details

Abstract

Facing the challenge of data explosion in the information age, statistics serves as a key data processing tool, yet its complex theories and models are often difficult for non-professionals to understand. To improve the understanding of abstract statistical concepts and theories among non-professionals, this paper discusses the application of the Animate package in R language for statistical visualization. This paper uses the package to realize the visualization of statistical methods such as K-means clustering and SVM classification, revealing the influence of parameter changes on clustering and classification results. Research results show that the Animate package effectively transforms abstract statistical concepts into intuitive dynamic graphics, and the application value in data analysis is verified through a practical case of SVM classification on the Wisconsin breast cancer dataset. Although Animate shows advantages and application potential in statistical visualization, it still has limitations in comprehensive applications. Future research further explores the application of Animate in broader statistical fields and develops advanced visualization tools to meet growing data analysis needs.

Keywords

Animate; R language; visualization; statistics

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Funding

2023 Guangxi Higher Education Undergraduate Teaching Reform Project (2023JGB329)

About the authors

Wang Qian (2002-), female, Han ethnicity, from Huai'an, Jiangsu, is currently pursuing a master's degree in machine vision; Pan Weiquan (1980-), male, Han ethnicity, from Pingnan, Guangxi, associate professor, PhD, research direction: statistics, probability theory, and mathematical statistics.