用乐高积木数据建立多元线性回归模型

IF 1.5 Q2 EDUCATION, SCIENTIFIC DISCIPLINES
Anna D. Peterson, Laura E. Ziegler
{"title":"用乐高积木数据建立多元线性回归模型","authors":"Anna D. Peterson, Laura E. Ziegler","doi":"10.1080/26939169.2021.1946450","DOIUrl":null,"url":null,"abstract":"Abstract We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the number of pieces, the theme (i.e., product line), and the general size of the pieces. By starting with graphical displays and simple linear regression, students are able to develop additive multiple linear regression models as well as interaction models to accomplish the task. We provide examples of student responses to the activity and suggestions for teachers based on our experiences. Supplementary materials for this article are available online.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":"29 1","pages":"297 - 303"},"PeriodicalIF":1.5000,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/26939169.2021.1946450","citationCount":"5","resultStr":"{\"title\":\"Building a Multiple Linear Regression Model With LEGO Brick Data\",\"authors\":\"Anna D. Peterson, Laura E. Ziegler\",\"doi\":\"10.1080/26939169.2021.1946450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the number of pieces, the theme (i.e., product line), and the general size of the pieces. By starting with graphical displays and simple linear regression, students are able to develop additive multiple linear regression models as well as interaction models to accomplish the task. We provide examples of student responses to the activity and suggestions for teachers based on our experiences. Supplementary materials for this article are available online.\",\"PeriodicalId\":34851,\"journal\":{\"name\":\"Journal of Statistics and Data Science Education\",\"volume\":\"29 1\",\"pages\":\"297 - 303\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/26939169.2021.1946450\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistics and Data Science Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/26939169.2021.1946450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistics and Data Science Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/26939169.2021.1946450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 5

摘要

摘要:我们提出了一个创新的活动,利用乐高积木的数据来帮助学生自我发现多元线性回归。引导学生预测在亚马逊网站上发布的乐高套装的价格(亚马逊价格),使用乐高的特征,如块的数量,主题(即产品线),以及块的一般尺寸。通过图形显示和简单的线性回归,学生能够建立相加的多元线性回归模型以及交互模型来完成任务。我们提供了学生对活动的反应示例,并根据我们的经验为教师提供建议。本文的补充材料可在网上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building a Multiple Linear Regression Model With LEGO Brick Data
Abstract We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the number of pieces, the theme (i.e., product line), and the general size of the pieces. By starting with graphical displays and simple linear regression, students are able to develop additive multiple linear regression models as well as interaction models to accomplish the task. We provide examples of student responses to the activity and suggestions for teachers based on our experiences. Supplementary materials for this article are available online.
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
Journal of Statistics and Data Science Education
Journal of Statistics and Data Science Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.90
自引率
35.30%
发文量
52
审稿时长
12 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信