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Journal of Statistics Education Volume 28, 2020 - Issue 1
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Articles

Causal Inference in Introductory Statistics Courses

Kevin CummiskeyDepartment of Mathematical Sciences, United States Military Academy, West Point, NYCorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0002-9537-3381
ORCID Icon,
Bryan AdamsDepartment of Mathematical Sciences, United States Military Academy, West Point, NY
,
James PleussDepartment of Mathematical Sciences, United States Military Academy, West Point, NY
,
Dusty TurnerDepartment of Mathematical Sciences, United States Military Academy, West Point, NYORCID Iconhttp://orcid.org/0000-0003-2998-8799
ORCID Icon,
Nicholas ClarkDepartment of Mathematical Sciences, United States Military Academy, West Point, NY
&
Krista WattsDepartment of Mathematical Sciences, United States Military Academy, West Point, NY
Pages 2-8 | Published online: 19 Feb 2020

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Read on this site (5)

Jeff Witmer. (2023) What Should We Do Differently in STAT 101?. Journal of Statistics and Data Science Education 0:0, pages 1-5.
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Yonggang Lu, Qiujie Zheng & Daniel Quinn. (2023) Introducing Causal Inference Using Bayesian Networks and do-Calculus. Journal of Statistics and Data Science Education 31:1, pages 3-17.
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Alex Reinhart, Ciaran Evans, Amanda Luby, Josue Orellana, Mikaela Meyer, Jerzy Wieczorek, Peter Elliott, Philipp Burckhardt & Rebecca Nugent. (2022) Think-Aloud Interviews: A Tool for Exploring Student Statistical Reasoning. Journal of Statistics and Data Science Education 30:2, pages 100-113.
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Bryan Adams, Daniel Baller, Bryan Jonas, Anny-Claude Joseph & Kevin Cummiskey. (2021) Computational Skills for Multivariable Thinking in Introductory Statistics. Journal of Statistics and Data Science Education 29:sup1, pages S123-S131.
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Karsten Lübke, Matthias Gehrke, Jörg Horst & Gero Szepannek. (2020) Why We Should Teach Causal Inference: Examples in Linear Regression With Simulated Data. Journal of Statistics Education 28:2, pages 133-139.
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Articles from other publishers (7)

Anton Sugolov, Eric Emmenegger, Andrew D. Paterson & Lei Sun. (2023) Statistical Learning of Large-Scale Genetic Data: How to Run a Genome-Wide Association Study of Gene-Expression Data Using the 1000 Genomes Project Data. Statistics in Biosciences.
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Kevin Cummiskey & Karsten Lübke. (2022) Causality in statistics and data science education. AStA Wirtschafts- und Sozialstatistisches Archiv 16:3-4, pages 277-286.
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Marta Benková, Dagmar Bednárová, Gabriela Bogdanovská & Marcela Pavlíčková. (2022) Redesign of the Statistics Course to Improve Graduates’ Skills. Mathematics 10:15, pages 2569.
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Andrew Forney & Scott Mueller. (2022) Causal inference in AI education: A primer. Journal of Causal Inference 10:1, pages 141-173.
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Hongcui Du & Alexandra List. (2022) Reasoning about text-based evidence. Contemporary Educational Psychology 68, pages 102038.
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Steven R. Jones & George E. Kuster. (2021) Examining students’ variational reasoning in differential equations. The Journal of Mathematical Behavior 64, pages 100899.
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Dennis K. Pearl & Lawrence M. Lesser. (2020) Statistical edutainment that lines up and fits. Teaching Statistics 43:1, pages 45-51.
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