RegLine: Assisting Novices in Refining Linear Regression Models

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

The process of verifying linear model assumptions and remedying associated violations is complex, even when dealing with simple linear regression. This process is not well supported by current tools and remains time-consuming, tedious, and error-prone. We present RegLine, a visual analytics tool supporting the iterative process of assumption verification and violation remedy for simple linear regression models. To identify the best possible model, RegLine helps novices perform data transformations, deal with extreme data points, analyze residuals, validate models by their assumptions, and compare and relate models visually. A qualitative user study indicates that these features of RegLine support the exploratory and refinement process of model building, even for those with little statistical expertise. These findings may guide visualization designs on how interactive visualizations can facilitate refining and validating more complex models.

Original languageEnglish
Title of host publicationProceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020
EditorsGenny Tortora, Giuliana Vitiello, Marco Winckler
PublisherAssociation for Computing Machinery
Publication date2020
Article number30
ISBN (Electronic)9781450375351
Publication statusPublished - 2020
Event2020 International Conference on Advanced Visual Interfaces, AVI 2020 - Salerno, Italy
Duration: 28 Sep 20202 Oct 2020


Conference2020 International Conference on Advanced Visual Interfaces, AVI 2020
SponsorACM Special Interest Group on Computer-Human Interaction (SIGCHI), ACM Special Interest Group on Hypertext, Hypermedia, and Web (SIGWEB), ACM Special Interest Group on Multimedia (SIGMM), Association for Computing Machinery (ACM)
SeriesACM International Conference Proceeding Series

    Research areas

  • data transformation, exploratory data analysis, linear regression, model verification and remedy, residual analysis

ID: 258326279