A gentle introduction to principal component analysis using tea-pots, dinosaurs, and pizza

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Edoardo Saccenti
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引用次数: 0

Abstract

Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions based on the data. As such, PCA can be an effective tool to increase students data literacy by providing a visual and intuitive way to understand and work with data. This article outlines a teaching strategy to introduce and explain PCA using basic mathematics and statistics together with visual demonstrations.
用茶壶、恐龙和披萨温和地介绍主成分分析法
主成分分析(PCA)是一种强大的统计技术,可以降低数据的复杂性,使数据中的模式和关系更容易理解。通过使用 PCA,学生可以学会识别数据集中最重要的特征,直观显示变量之间的关系,并根据数据做出明智的决策。因此,PCA 可以提供一种理解和处理数据的形象直观的方法,是提高学生数据素养的有效工具。本文概述了一种教学策略,即利用基础数学和统计学知识以及直观演示来介绍和解释 PCA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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