In 2016, the ASA released an historic statement on statistical significance and p values in an effort to improve the conduct and interpretation of quantitative science and inform the growing emphasis on reproducibility of science research. That statement garnered vast attention, accumulating more than 190,000 page views, and generated discussion among statisticians in academia, government, and business worldwide. ASA continues to foster the dialogue and steer research and understanding at a new scientific conference this fall.
What: Symposium on Statistical Inference (SSI) #SSI2017
When: October 11-13, 2017
Where: Bethesda, Maryland
Why: Moving beyond the "Don'ts" referenced in the ASA statement (the inappropriate interpretations and uses of p-values and significance tests) the SSI will focus on the "Do's." Discussions will center on specific approaches to improving statistical practice as it intersects with three broad components of research activities.
- Steve Goodman, professor of medicine and of health research and policy, associate dean for clinical and translational research, Stanford University School of Medicine
- John Ioannidis, professor of medicine and of health research and policy, director of the Stanford Prevention Research Center, Stanford University
- Andrew Gelman, professor of statistics and political science, director of the Applied Statistics Center, Columbia University
- Xiao-Li Meng, dean of the Graduate School of Arts and Sciences, Whipple V. N. Jones Professor of Statistics, Harvard University
- Marcia McNutt, president, National Academy of Sciences (tentative)
Media can attend SSI for FREE but must pre-register by contacting Jill Talley, ASA Public Relations Manager, at email@example.com. Scientists and media interested in learning more about statistical significance and the challenge of reproducibility in scientific research are encouraged to sign up for the ASA mailing list. ###
For more information: Jill Talley Public Relations Manager, ASA O: (703) 684-1221, Ext. 1865 firstname.lastname@example.org