Stats, Optimization, and Machine Learning Seminar - The Reproducibility Crisis, pt 1

First part of our series on the reproducibility crisis:

Peter Shaffery will present Simmons, Nelson, and Simonsohn's seminal 2011 article "False Positive Psychology" (http://journals.sagepub.com/doi/abs/10.1177/0956797611417632)

Here's a quick blog post that treads some similar ground, people may want to look at that ahead of time if they're curious (http://blogs.plos.org/absolutely-maybe/2016/04/25/5-tips-for-avoiding-p-value-potholes/)

Abstract of Simmons et al:

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In this article, we accomplish two things. First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process