The ladder of abstraction in statistical graphics
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908533943959552 |
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| author | Gelman, Andrew |
| author_facet | Gelman, Andrew |
| contents | Graphical forms such as scatterplots, line plots, and histograms are so familiar that it can be easy to forget how abstract they are. As a result, we often produce graphs that are difficult to follow. We propose a strategy for graphical communication by climbing a ladder of abstraction (a term from linguistics that we borrow from Hayakawa, 1939), starting with simple plots of special cases and then at each step embedding a graph into a more general framework. We demonstrate with two examples, first graphing a set of equations related to a modeled trajectory and then graphing data from an analysis of income and voting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_06920 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The ladder of abstraction in statistical graphics Gelman, Andrew Methodology Graphical forms such as scatterplots, line plots, and histograms are so familiar that it can be easy to forget how abstract they are. As a result, we often produce graphs that are difficult to follow. We propose a strategy for graphical communication by climbing a ladder of abstraction (a term from linguistics that we borrow from Hayakawa, 1939), starting with simple plots of special cases and then at each step embedding a graph into a more general framework. We demonstrate with two examples, first graphing a set of equations related to a modeled trajectory and then graphing data from an analysis of income and voting. |
| title | The ladder of abstraction in statistical graphics |
| topic | Methodology |
| url | https://arxiv.org/abs/2501.06920 |