quartets

In the spirit of Anscombe's quartet, this package includes datasets that demonstrate the importance of visualizing your data, the importance of not relying on statistical summary measures alone, and why additional assumptions about the data generating mechanism are needed when estimating causal effects. The package includes "Anscombe's Quartet" (doi:10.1080/00031305.1973.10478966), D'Agostino McGowan & Barrett (2023) "Causal Quartet" (doi:10.48550/arXiv.2304.02683), "Datasaurus Dozen" (Matejka & Fitzmaurice 2017), "Interaction Triptych" (Rohrer & Arslan 2021) (doi:10.1177/25152459211007368), "Rashomon Quartet" (Biecek et al. 2023) (doi:10.48550/arXiv.2302.13356), and Gelman "Variation and Heterogeneity Causal Quartets" (Gelman et al. 2023) (doi:10.48550/arXiv.2302.12878).

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