UCLA Department of Statistics Seminar Series
Tue, 10/13/2015, 2:00 PM—3:00 PM
3656 Geology Bldg.
Joel A. Tropp
Computing & Mathematical Sciences
California Institute of Technology
Applied Random Matrix Theory
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics. Therefore, it is desirable to have tools for studying random matrices that are flexible, easy to use, and powerful. Over the last fifteen years, researchers have developed a remarkable family of results, called matrix concentration inequalities, that balance these criteria. This talk offers an invitation to the field of matrix concentration inequalities.
Social Statistics Seminar Series
Thu, 10/15/2015, 2:00 PM—3:00 PM
4240 Public Affairs Building
Inferring and understanding travel and migration movements at a global scale
Despite extensive work on the dynamics and outcomes of large-scale migrations, timely and accurate estimates of population movements do not exist. While censuses, surveys, and observational data have been used to measure migration, estimates based on these data sources are constrained in their inability to detect unfolding migrations, and lack temporal and demographic detail.
In this study, we present a novel approach for generating estimates of migration that can measure movements of particular demographic groups across country lines. Specifically, we model migration as a function of long-term moves across countries using aggregated Facebook data.
We demonstrate that this methodological approach can be used to produce accurate measures of past and ongoing migrations - both short-term patterns and long-term changes in residence. Several case studies confirm the validity of our approach, and highlight the tremendous potential of information obtained from online platforms to enable novel research on human migration events.
Master of Applied Statistics Program approved with first students in Fall 2016!
We are excited to announce that our Master of Applied Statistics program has received final approval from the UC President and becomes the newest program offered by the department.
The Master of Applied Statistics (MAS) program was created in response to the increasingly high demand from students seeking a terminal master’s degree in data science and quantitative analytics.
The MAS program will prepare students for work in industry through an emphasis on methods and theory commonly used in applications. The MAS will cater primarily to part-time students. Courses for the new program will be offered in the evening, so that professionals can continue working while completing their degrees. The degree will require a thesis project that will involve working closely with an industry partner and a faculty member to solve a real scientific or business problem. This will
often be in the field where the student is working, thus deepening their understanding of it. The Department has various business, industry and government partners to provide internships, thesis topics, support for their employees, and job prospects for graduating students.
Applications will be accepted starting in the late Fall of 2015 for students wishing to begin the program in the Fall of 2016.
We welcome companies or agencies that are interested in working with the MAS Program.
Two UCLA Statistics student teams have won prizes in the Undergraduate Statistics Project Competition
Two UCLA Statistics student teams have won prizes in the Undergraduate Statistics Project Competition, sponsored by CAUSE, the Consortium for Advancement in Undergraduate Statistics Education. Students Fangbo Xu, Jia Liu and Ran Bi won third place for their project "Electricity Consumption in Chicago". They are being invited to give a plenary talk at the First Annual Electronic Undergraduate Statistics Research Conference on October 2.
Noam Habot, Uriel Ocampo, Qiuchi Chen and Alberto Reyes won an Honorable Mention in the category of Undergraduate Statistics Class Project Competition for "Crowdlending for Investors: Yay or Nay", and have been invited to present a virtual poster at the Undergraduate Statistics Research Conference.
Congratulations to these students, directed by Dr. Dai Trang Le.