用茶壶、恐龙和披萨温和地介绍主成分分析法

IF 1.2 Q2 EDUCATION & EDUCATIONAL RESEARCH Teaching Statistics Pub Date : 2024-01-03 DOI:10.1111/test.12363
Edoardo Saccenti
{"title":"用茶壶、恐龙和披萨温和地介绍主成分分析法","authors":"Edoardo Saccenti","doi":"10.1111/test.12363","DOIUrl":null,"url":null,"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.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A gentle introduction to principal component analysis using tea-pots, dinosaurs, and pizza\",\"authors\":\"Edoardo Saccenti\",\"doi\":\"10.1111/test.12363\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":43739,\"journal\":{\"name\":\"Teaching Statistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teaching Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/test.12363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teaching Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/test.12363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

摘要

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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A gentle introduction to principal component analysis using tea-pots, dinosaurs, and pizza
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Teaching Statistics
Teaching Statistics EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.10
自引率
25.00%
发文量
31
期刊最新文献
The sample is not the population In praise of pioneers Fear of the unknown: Relationship between statistics anxiety and attitudes toward statistics of university students in three countries Tribute to Jim Ridgway and his contributions to statistics education and statistical literacy Introduction to the Bayes factor: A Shiny/R app
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1