Seminars & Colloquia

Jeff Leek

Johns Hopkins Bloomberg School of Public Health

"Is Most Published Research Really False?"

Wednesday November 02, 2016 07:00 PM
Location: Mountains Ballroom, Talley Student Union
(Visitor parking instructions)

This talk is part of the Data Science series



The accuracy of published research is critical for scientists, physicians and patients who rely on these results. But the fundamental belief in the scientific literature was called into serious question by a paper suggesting most published medical research is false. This claim has launched an entire discipline focused on the crisis of reproducibility and replicability of science. In this talk I will discuss two major open problems inspired by this scientific crisis: how do we know when a study replicates and what is the rate of false discoveries in the scientific literature? In answering these questions I will argue that much of the crisis in science can be attributed to misunderstanding statistics.

Short Bio:

Jeff Leek is an Assistant Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in Biostatistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome Biology, and PLoS Medicine. He created Data Analysis as a component of the year-long statistical methods core sequence for Biostatistics students at Johns Hopkins. The course has won a teaching excellence award, voted on by the students at Johns Hopkins, every year Dr. Leek has taught the course.

Special Instructions: Poster Session 5-7 and 8-9 This RED talk will coincide with a Data Science Poster Session immediately before and afterwards, and will also include a reception afterwards in the Piedmont Ballroom.The poster session is open any research or application by NC State faculty, students, or staff in data science, broadly interpreted. For more information, and to sign-up to participate, email

Host: Trey Overman, Data Science Initiative

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