"A Second Statistics Course is Needed: What should it be?"
with Marc Isaacson and Milo Schield, Augsburg College
Recording
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Abstract
Big data, AP stats and the common core are driving the need for a "second" statistics course. What should it be? Isaacson will argue for a Statistical Literacy course that emphasizes breadth. Schield will argue for an advanced-topics follow-on course that emphasizes depth. Isaacson will argue that the traditional inference course doesn't have time for important topics such as coincidences, confounding, evaluating surveys and studies, and "Where do statistics come from?" so a statistical literacy course is needed. Schield will argue that the 50% of college graduates who are in quantitative majors and are required to take a statistical inference course need a follow-on applications course. This course should focus on inference-related applications (ANOVA and web analytics), modelling (linear and logistic regression), simulation (boot strapping and financial modeling) and other advanced topics (factor and cluster analysis; epidemiology and causation in observational studies). Participants will be given specific examples of each topic so they can better appreciate their value to students. Participants will be invited to support either side or both during the presentation. [Schield has taught the advanced modelling course using linear and logistic regression, an MBA course in quantitative methods, and is using web analytics to make business decisions. Isaacson developed the first Statistical Literacy course online and the first Statistical Literacy for Managers course.]
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