The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R
When students learn linear regression, they must learn to use diagnostics to check and improve their models. Model-building is an expert skill requiring the interpretation of diagnostic plots, an understanding of model assumptions, the selection of appropriate changes to remedy problems, and an intu...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | Journal of Statistics and Data Science Education |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/26939169.2025.2520202 |
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| author | Alex Reinhart |
| author_facet | Alex Reinhart |
| author_sort | Alex Reinhart |
| collection | DOAJ |
| description | When students learn linear regression, they must learn to use diagnostics to check and improve their models. Model-building is an expert skill requiring the interpretation of diagnostic plots, an understanding of model assumptions, the selection of appropriate changes to remedy problems, and an intuition for how potential problems may affect results. Simulation offers opportunities to practice these skills, and is already widely used to teach important concepts in sampling, probability, and statistical inference. Visual inference, which uses simulation, has also recently been applied to regression instruction. This article presents the regressinator, an R package designed to facilitate simulation and visual inference in regression settings. Simulated regression problems can be easily defined with minimal programming, using the same modeling and plotting code students may already learn. The simulated data can then be used for model diagnostics, visual inference, and other activities, with the package providing functions to facilitate common tasks with a minimum of programming. Example activities covering model diagnostics, statistical power, and model selection are shown for both advanced undergraduate and Ph.D.-level regression courses. |
| format | Article |
| id | doaj-art-06fa6cbe3af84f0dae44625798d730ea |
| institution | Kabale University |
| issn | 2693-9169 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Statistics and Data Science Education |
| spelling | doaj-art-06fa6cbe3af84f0dae44625798d730ea2025-08-20T03:44:54ZengTaylor & Francis GroupJournal of Statistics and Data Science Education2693-91692025-08-0111310.1080/26939169.2025.2520202The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in RAlex Reinhart0Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PAWhen students learn linear regression, they must learn to use diagnostics to check and improve their models. Model-building is an expert skill requiring the interpretation of diagnostic plots, an understanding of model assumptions, the selection of appropriate changes to remedy problems, and an intuition for how potential problems may affect results. Simulation offers opportunities to practice these skills, and is already widely used to teach important concepts in sampling, probability, and statistical inference. Visual inference, which uses simulation, has also recently been applied to regression instruction. This article presents the regressinator, an R package designed to facilitate simulation and visual inference in regression settings. Simulated regression problems can be easily defined with minimal programming, using the same modeling and plotting code students may already learn. The simulated data can then be used for model diagnostics, visual inference, and other activities, with the package providing functions to facilitate common tasks with a minimum of programming. Example activities covering model diagnostics, statistical power, and model selection are shown for both advanced undergraduate and Ph.D.-level regression courses.https://www.tandfonline.com/doi/10.1080/26939169.2025.2520202Regression diagnosticsResidual analysisTidy dataVisual inference |
| spellingShingle | Alex Reinhart The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R Journal of Statistics and Data Science Education Regression diagnostics Residual analysis Tidy data Visual inference |
| title | The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R |
| title_full | The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R |
| title_fullStr | The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R |
| title_full_unstemmed | The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R |
| title_short | The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R |
| title_sort | regressinator a simulation tool for teaching regression assumptions and diagnostics in r |
| topic | Regression diagnostics Residual analysis Tidy data Visual inference |
| url | https://www.tandfonline.com/doi/10.1080/26939169.2025.2520202 |
| work_keys_str_mv | AT alexreinhart theregressinatorasimulationtoolforteachingregressionassumptionsanddiagnosticsinr AT alexreinhart regressinatorasimulationtoolforteachingregressionassumptionsanddiagnosticsinr |