Journal of Statistics and Data Science Education · 2022 · 18 citations · 26 references
ManagementData ScienceScience EducationKnowledge SharingStatisticsTeamworkCollaborative Knowledge CreationCollaborative Knowledge SharingCollaborative LearningData Science EducationExpertise SharingStatistical ReasoningConceptual Understanding Of StatisticsInterdisciplinary ProjectsShared Knowledge ConstructionShared Understanding
Statisticians and data scientists have been called upon to increase the impact they have through their collaborative projects. Statistics and data science practitioners and their educators can achieve and enable greater impact by learning how to create shared understanding with their collaborators as well as teaching this concept to their students, colleagues, and mentees. In this article, we explore and explain the concepts of common knowledge and shared understanding, which is the basis for action to accomplish greater impacts. We also explore related concepts of misunderstanding and doubtful understanding. We describe a process for teaching oneself and others how to create shared understanding. We conclude that incorporating the concept of shared understanding into one’s practice of statistics or data science and following the steps described will result in having more impact on projects and throughout one’s career.
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Robert J. Aumann · The Annals of Statistics · 1976 · 2.5K citations
Causal diagrams for empirical research
Judea Pearl · Biometrika · 1995 · 2.3K citations
Zermelo and the Early History of Game Theory
Ulrich Schwalbe, Paul Walker · Games and Economic Behavior · 2001 · 170 citations · Full text