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P-values are overvalued or misinterpreted altogether, and the Questions are poorly formulated, too many tests are conducted, Identify just a sample of the issues underlying these sentiments: There areĬoncerns about scientists’ inability to replicate published resultsĪnd the cost to society of an ineffective scientific process. Half agreeing that it is a major crisis (Baker 2016). There is a crisis in reproducibility in science with more than In fact, 90% of 1576 researchers surveyed agreed that Statisticians and others are in general agreement that the current system of curating scientific knowledge is flawed (SterneĪnd Smith 2001 Leek and Peng 2015 Wasserstein and LazarĢ016). A Prescription for a Post-p < 0.05 Era: Teach Scientific information that we develop during the course.ġ. We provide ideas for expanding beyond the traditional classroom, two exampleĪctivities, and a course syllabus as well as the set of statistical best practices for creating and consuming World, leveraging simulation-based approaches to perform customized analyses and evaluate the behavior The course we have developed follows the story of how we use data to understand the Make statistical errors, the meaning of a single test within a research project, ways in which p-values workĪnd don’t work as expected, the role of stat istics in the lifecycle of science, and best practices for statisticalĬommunication. Speed up the process of gaining statistical wisdom by giving students insight into the human propensity to That expand our view of what constitutes the domain of statistics and thereby bridge undergraduate statistics coursework and the graduate student experience of applying statistics in research. Our prescription for a Post-p < 0.05 Era is to develop and teach courses
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Statisticians are in general agreement that there are flaws in how science is currently practiced there is lessĪgreement in how to make repairs. Professor Emeritus, University of Washington, Seattle, WA PNW Research Lab, USDA Science Center, Seattle, WA b Northwest Fisheries Science Center, Seattle, WA c Norwegian Computing Center, Oslo, Norway Ashley Steela, Martin Liermannb, and Peter Guttorpc,d S1, 392–401: Statistical Inference in the st Centuryīeyond Calculations: A Course in Statistical ThinkingĮ. Ashley Steel, Martin Liermann & Peter Guttorp (2019) BeyondĬalculations: A Course in Statistical Thinking, The American Statistician, 73:sup1, 392-401, DOI:įull Terms & Conditions of access and use can be found atĢ019, VOL. Ashley Steel, Martin Liermann & Peter Guttorp ISSN: 0003-1305 (Print) 1537-2731 (Online) Journal homepage: īeyond Calculations: A Course in StatisticalĮ.