Using simulation‐based inference for learning introductory statistics. (26th May 2014)

• Record Type: Journal Article
• Authors: Rossman, Allan J.; Chance, Beth L.
• Is Part Of: Wiley interdisciplinary reviews. Volume 6:Number 4(2014)
• Page Start: 211
• Page End: 221
• Publication Date: 2014-05-26
• Subjects: Mathematical statistics -- Data processing -- Periodicals; Science -- Data processing -- Periodicals; Social sciences -- Data processing -- Periodicals; Mathematical statistics -- Periodicals; 519.50285
• DOI: 10.1002/wics.1302
• Languages: English
• ISSNs: 1939-5108

Abstract

<abstract abstract-type="main" id="wics1302-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="wics1302-para-0001">Recent curriculum development projects emphasize teaching simulation and randomization‐based statistical inference as a prominent feature in introductory statistics courses. We describe the goals, distinctive features, and examples from some of these projects. Technology is a key component of these courses, so we mention desirable features of the various technology products used with this approach. We also discuss how student learning is being assessed in such courses, along with how the curriculum effort itself is being evaluated. We also touch on some challenges that we have encountered with teaching these courses, both from a student and a faculty viewpoint. <italic>WIREs Comput Stat</italic> 2014, 6:211–221. doi: 10.1002/wics.1302</p> <p>For further resources related to this article, please visit the <ext-link ext-link-type="uri" xlink:href="http://wires.wiley.com/remdoi.cgi?doi=10.1002/wics.1302" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">WIREs website</ext-link>.</p> <p id="wics1302-para-0002">Conflict of interest: The authors have declared no conflicts of interest for this article.</p> </abstract>