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Data, Won't You Be My Valentine? How to Lovingly Collect, Interpret, and Analyze Data in Higher Education
Dr. Alexandros M. Goudas
There is a serious reproducibility problem in medical journals (Ioannidis, 2005) and psychology journals (Nosek, 2015). That means we will have trouble relying on millions of peer-reviewed articles’ results. The same applies to findings in many publications in higher education. Much of this is due to inadvertent p-hacking: i.e., biased ways of collecting, analyzing, and interpreting data. This webinar will be a primer on how to start (lovingly) interpreting articles and analyzing your own data using sound principles, with the goal of avoiding bias in higher education data. Celebrate Valentine’s Day with data!
Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Med 2(8): e124. Retrieved from
Nosek, B. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). Retrieved from
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