Combating Anti-Statistical Thinking Using Simulation-Based Methods Throughout the Undergraduate Curriculum

Nathan Tintle, Beth Chance, George Cobb, Soma Roy, Todd Swanson and Jill VanderStoep

The American Statistician, 2015, vol. 69, issue 4, 362-370

Abstract: The use of simulation-based methods for introducing inferen-ce is growing in popularity for the Stat 101 course, due in part to increasing evidence of the methods ability to improve studen-ts’ statistical thinking. This impact comes from simulation-based methods (a) clearly presenting the overarching logic of inference, (b) strengthening ties between statistics and probability/mathematical concepts, (c) encouraging a focus on the entire research process, (d) facilitating student thinking about advanced statistical concepts, (e) allowing more time to explore, do, and talk about real research and messy data, and (f) acting as a firm-er foundation on which to build statistical intuition. Thus, we argue that simulation-based inference should be an entry point to an undergraduate statistics program for all students, and that simulation-based inference should be used throughout all under-graduate statistics courses. To achieve this goal and fully recognize the benefits of simulation-based inference on the undergraduate statistics program, we will need to break free of historical forces tying undergraduate statistics curricula to mathematics, consider radical and innovative new pedagogical approaches in our courses, fully implement assessment-driven content innovations, and embrace computation throughout the curriculum.[Received December 2014. Revised July 2015]

Date: 2015
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DOI: 10.1080/00031305.2015.1081619

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