Victor De la Peña
Students will have the possibility of working on projects involving
applications of Probability and Statistics to Problems in Earth
Sciences including projects such as the tele-conections between El Nino
and the Indian Monsoon.
Andrew Gelman
Several projects involving political science, economics, sociology, psychology, public health, and policy; for examples, see http://www.stat.columbia.edu/~gelman/blog/.
Ji Meng Loh
Current
theories in cosmology attempt to describe the evolution of the universe
from its beginning to its present state. In particular, comoslogists
are interested in the understanding the clustering of matter that
exists in the universe today and how this clustering may have developed
from the universe's original homogeneous state. By studying the
clustering properties of matter in the universe today, we can
differentiate between the various cosmological theories. Furthermore,
these theories depend on certain parameters that describe fundamental
properties of the universe (e.g. the matter density). The values of
these parameters are still uncertain. By comparing the clustering of
matter predicted by the theories with the observed clustering, we can
estimate the values of these parameters.
This goal of this
project is to study current methods for estimating clustering and to
develop methods for improved estimation. The student involved with this
project will mainly conduct statistical analyses on existing datasets
(such as galaxy surveys) as well as run simulation studies to compare
current and new methods of estimating clustering.
Requirements - knowledge of statistics, experience with programming (e.g. in C, R or matlab). Interest in astronomy a plus.
Daniel Rabinowitz
A
variety of opportunities for supervised experience in data analysis in
support of research projects in the Arts & Sciences, the School of
Public Health, the School of Social work, and the Medical and Nursing
Schools.
Jan Vecer
Statistics
in Sports: Projects for undergraduate students are available in the
direction of statistics in sports. The students will get familiar with
statistical techniques necessary for the analysis of sports data and
apply it in one of the sports, such as in basketball, football, hockey,
soccer, tennis, golf, etc.
Dr. Tian Zheng
Research
experience for undergraduates/Master students: Projects from various
areas in statistical genetics, bioinformatics, and computational
biology are available for undergraduates and MA/MS students. Students
who are interested should be comfortable with statistical inference
concepts and basic computer programming.
