quartets: Datasets to Help Teach Statistics
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" (Anscombe 1973) <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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