An Interactive Introduction to Causal Inference

Lucius E.J. Bynum (New York University) , Falaah Arif Khan (New York University) , Oleksandra Konopatska (Ukrainian Catholic University) , Joshua R. Loftus (London School of Economics) , Julia Stoyanovich (New York University)
September 21, 2022

Published at VISxAI 2022: Workshop on Visualization for AI Explainability.

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Acknowledgments

This work was supported in part by NSF awards 1922658, 1934464 and 1916505, and by Pivotal Ventures.

Author Contributions

Writing and Exposition: Lucius, Julia, and Joshua.

Code, Diagrams, and Interactivity: Lucius and Oleksandra.

Illustrations: Falaah.

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY-ND 4.0. Source code is available at https://github.com/lbynum/interactive-causal-inference, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Bynum, et al., "An Interactive Introduction to Causal Inference", VISxAI: Workshop on Visualization for AI Explainability, 2022

BibTeX citation

@article{bynum2022interactive,
  author = {Bynum, Lucius E.J. and Khan, Falaah Arif and Konopatska, Oleksandra and Loftus, Joshua R. and Stoyanovich, Julia},
  title = {An Interactive Introduction to Causal Inference},
  journal = {VISxAI: Workshop on Visualization for AI Explainability},
  year = {2022},
  note = {https://lbynum.github.io/interactive-causal-inference},
  publisher = {IEEE}
}