Building a Multiple Linear Regression Model With LEGO Brick Data

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 li...

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Bibliographic Details
Published inJournal of Statistics and Data Science Education Vol. 29; no. 3; pp. 297 - 303
Main Authors Peterson, Anna D., Ziegler, Laura
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis 02.09.2021
Taylor & Francis Ltd
Taylor & Francis Group
Subjects
Additive models
Costs
Datasets
Distance Education
Educational Benefits
Indicator variables
Interaction
Learning
Multivariate Analysis
Multivariate thinking
Prediction
Purchasing
Regression (Statistics)
Regression analysis
Science education
Statistics Education
Student retention
Teaching Methods
Toys
Undergraduate Students
Variables
Visual Aids
Web Sites
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Summary: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.
ISSN:2693-9169
2693-9169
DOI:10.1080/26939169.2021.1946450