Sonia Petrone, the new Editor of Statistical Science, writes:
It is an honor and an exciting challenge to be the new Editor of Statistical Science. I would like to thank the Past Editor Cun-Hui Zhang for his generous help in the transition, and for the great vitality he is leaving to the journal, including a forthcoming special issue on causal inference and a special section on network data.
I will continue in the tradition of Statistical Science, aiming at conveying a vision of the “full range of contemporary statistical thought at a moderate technical level accessible to our wide community”. I will do my best to enhance the features that make Statistical Science so unique and appreciated.
Let me first express my intention to contribute to giving the deserved space to women in statistics. More to come about this, but certainly this is something I particularly care about, and that I hope the journal will address, in the appropriate ways.
Recognizing the huge value of review articles has been a founding principle of Statistical Science, and a reason for its success. I would like to renew the call for good review articles, along the lines well expressed in the Editorials of Robert E. Kass (1992) and George Casella (2002). If you are considering writing a review article, you may submit a detailed outline to the Editor or to any member of the Editorial Board for early feedback. Also, any reader is welcome to contact us with suggestions, for example, informing us of a lecture that may be the basis for an interesting review paper, or of topics that they would like to see reviewed and discussed in the journal.
I would like to particularly encourage submissions of interdisciplinary articles, or proposals for special sections or issues, that could offer different perspectives on a problem—for example, synthesizing probabilistic and statistical methodologies on a problem of interest, or statistical and machine learning approaches, or discussing why should statisticians care about a particular mathematical area.
In his Editorial in the first issue of Statistical Science, Morris DeGroot wrote, “The field of Statistics is in a state of rapid growth and expansion. As a result [statisticians are] more and more specialized. A central purpose of Statistical Science is to convey the richness, breadth and unity of the field.” It couldn’t have been said better, or more simply. Nowadays, we are still facing a trend towards specialization; but it’s not only that. People are being attracted to new fields—machine learning and AI are obvious examples—that have a lot in common with statistics (and I feel are somehow “evolving back” towards statistics), and that, at the same time, bring different viewpoints and problems. To “convey the richness, breadth, and unity,” good interdisciplinary articles, or articles from a related field yet written for statisticians, would be stimulating and appreciated.
These are some directions for the journal I had started working on. But there is something that has been weighing on my mind in these weeks, and I think we should be prepared to discuss it in Statistical Science. In these dramatic days, many of us are offering their work and expertise in projects and initiatives in the urgent struggle against COVID-19 [see the articles here and here]. But we are also reflecting on our role and impact, now and in the future, to help prevent this from happening again. I believe we have a lot to learn from this terrible crisis.
We are planning to host a discussion in Statistical Science, in a special issue, that will offer a thoughtful and constructive reflection on the role of statistics in the COVID-19 crisis, in its many aspects. Statistics and related fields drive the most advanced scientific studies towards a vaccine, as well as effective and shared data collection, and a proper and timely evaluation of risk and support to make decisions. To what extent are we having an impact in all this? What should be improved? Is this crisis changing our perspective on our research and work? Chiara Sabatti (Stanford University) is kindly available to help coordinate contributions, as a guest co-editor of a special issue. You are welcome to contact me (email@example.com)and Chiara (firstname.lastname@example.org) with your thoughts on this.
In the meantime, life goes on and it is full of interesting challenges and topics for discussion: I see a lot of exciting work on the horizon for Statistical Science!