Statistics Professor Babak Shahbaba has been awarded a $1.7 million National Institutes of Health (NIH) grant that could have far-reaching implications for future efforts to address memory impairment. The research involves electrophysiological experiments in rats to study how a brain structure — the hippocampus — supports our ability to remember the daily events of our life. Furthermore, the research should lead to new methodologies for handling huge amounts of complex data. The five-year grant, “Scalable Bayesian Stochastic Process Models for Neural Data Analysis,” is a multidisciplinary collaboration between Shahbaba and fellow Statistics Professor Hernando Ombao and Associate Professor of Neurobiology and Behavior Norbert Fortin.
Statistics Professor Vladimir Minin recently organized a special section on infectious diseases in Statistical Science in collaboration with Theodore Kypraios, an associate professor of mathematics at the University of Nottingham. The section, written for the broader statistical community, covers the state-of-the-art of statistical inference for stochastic epidemic models for infectious disease data. It includes the following six articles:
A great point about this was made about a decade ago by Andrew Gelman, a professor in the Department of Statistics and Department of Political Science at Columbia University, and Hal Stern, a professor in the Department of Statistics at the University of California, Irvine, in their wonderfully titled article “The Difference Between ‘Significant’ and ‘Not Significant’ is not itself Statistically Significant.”
In their discussion, Gelman and Stern touch on the growing awareness that “statistical significance is not the same as practical importance,” and “that dichotomization into significant and nonsignificant results encourages the dismissal of observed differences in favor of the usually less interesting null hypothesis of no difference, and that any particular threshold for declaring significance is arbitrary.”
Read the full story at The Lakeland Times.
What role do statisticians play in governing? A pretty important one, according to Statistics Professor Jessica Utts. The 2016 President of the American Statistical Association (ASA) gave a keynote speech in Sri Lanka titled “The Importance of Statistics for Good Governance and What the ASA is Doing to Help.” The speech was delivered in December at the Institute of Applied Statistics Sri Lanka International Conference (IASSL-IC), which was themed, “Statistics for Good Governance.” IASSL is a nonprofit organization that aims to support the professional development of statisticians and statistical education in Sri Lanka.
As reported by Shannon Jayawardena, Utts explained in her keynote that “good governance means making decisions that benefit the constituents in an efficient and effective way.” Regardless of the organization’s size or structure – whether you’re governing a nation or small club — “data and statistical knowledge should play a major role in the process of making decisions and setting policy,” said Utts. However, she also noted that this requires “good” data, and while “collecting massive amounts of data has become easy, collecting good data remains difficult.”
This is where statisticians can help in a variety of ways. First, Utts said that they can help organizations understand the difference between good and bad data, which is “crucial for good governance.” Second, they can help “educate people, ranging from politicians and policymakers to the general public, on the appropriate use and interpretation of data.” Finally, they can “play a major role in improving statistical methods for more efficient and accurate data collection and analysis.”
— Shani Murray
Professors Kurt Squire, Ramesh Jain and Vladimir Minin provide a sneak peak of what technological innovations are ahead in 2018.
Vladimir Minin, Professor of Statistics, joined the ICS faculty in July 2017.
Statistics Professor Jessica Utts and eight statistics graduate students (seven Ph.D. and one M.S.) attended the American Statistical Association’s 2017 Women in Statistics and Data Science Conference held in La Jolla, Calif., from Oct. 19-21. In its third year, the conference had about 400 attendees and is modeled after the Grace Hopper Conference, which is aimed more toward women in computing and computer sciences. According to Utts, UCI was probably the most well-represented school at the conference this year, with the nine women attending from the Department of Statistics as well as other women from across campus.
Graduate statistics student Shuying Zhu is the recipient of the 2017 Robert L. Newcomb Memorial Endowed Graduate Award, which aims to provide statistical support to researchers and advance the careers of graduate students in the Donald Bren School of ICS. Zhu previously studied chemical engineering in China, but she found statistics to be “useful and interesting.” A friend who studied at UC Irvine recommended the statistics program, so Zhu looked into it and realized it was a good program. She says Irvine is a nice place, and in her free time she enjoys playing badminton and tennis. She is interested in applied statistics and appreciates having the chance to learn. She plans to apply for a Ph.D. program and wants to start a career in academia. Zhu was “very surprised and grateful” to learn she had received the Newcomb award.
The 2017 Outstanding TA Award in Statistics went to Alexandra Peterson, a third-year Ph.D. student in the Department of Statistics. According to Peterson, being a good TA requires more than just a solid understanding of the course material. TAs should also be able to “provide several different understandable explanations for the students,” she says. Peterson adds that “it is also important to seem approachable so that students feel comfortable asking questions.”
Brandon Berman received Honorable Mention.