Teaching Simpson’s Paradox, Confounding, and Causal Inference
Created 06 Sep 2022| Updated 06 Dec 2023
| 30 articles
Multivariate thinking is important in statistics and data science education. Simpson’s Paradox, confounding, and causal inference are key topics that build on students’ prior statistical understanding. This collection highlights papers that have been published recently and in past decades which lays out approaches to help prepare students to make sense of the multivariate data around them. (Illustrative figure from “Might Temporal Logic Improve the Specification of Directed Acyclic Graphs (DAGs)?” by Ellison (JSDSE, 2021).)
Edited by
Nicholas J. Horton(Amherst College)
Journal of Statistics and Data Science Education (Vol., Iss., 2022)
Teaching Simpson’s Paradox, Confounding, and Causal Inference
Teaching Simpson’s Paradox, Confounding, and Causal Inference
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