Institute for Pure and Applied Mathematics
University of California, Los Angeles
Data Visualization and its Role in the Practice of Statistics
The Second Annual Undergraduate
June 17-24, 2006
Applications due: April 21, 2006 (updated)
[ Printable flyer ]
Mark Hansen (UCLA)
Vijay Nair (UM)
Deborah Nolan (UCB)
Doug Nychka (NCAR)
Duncan Temple Lang (UCD)
Bin Yu (UCB)
The first Summer Statistics Program was held in
2005. Read a complete summary of the event.
Statistics: The Science of Data
Today, almost every aspect of our lives is "rendered"
in data. New data collection technologies have made it easy to record
continuous, high-resolution measurements of our physical
environment (weather patterns, seismic events,
the human genome).
We're also constantly monitoring
our movements through and interactions with
our physical surroundings (automobile and air traffic, large-scale
land use, advanced manufacturing facilities).
In computer-mediated settings, our activities either depend
crucially on or consist entirely of complex digital data (networked games,
peer-to-peer technologies, Web site and Internet usage).
As a reflection of the
diversity and variety of the "systems" under study, these data-based
descriptions of our world tend to be massive in size, dynamic in
character, and replete with rich structures. The advent of these
enormous repositories of information presents us with an
interesting challenge: how can we represent and interpret such
complex, abstract and often socially important data?
The role of visualization
The theme of our Summer Program is visualization and its role
in the practice of statistics. Visualization and statistical graphics are
at the core of
exploratory data analysis, and in turn shape how we think about a particular
application, the models we entertain and the kinds of theory we
propose. Over the course of our seven day program, we will highlight a
number of statistical
applications, and with each we will consider novel approaches to
visualization that help guide our insight about the underlying statistical
questions. Through computer lab sessions that draw on each day's application,
students will receive
a basic introduction to statistical computing, providing them with
the skills to perform simple data manipulations, conduct exploratory analyses
and create informative visualizations.
The seven day workshop is designed so that students get
a sense of how statisticians approach large, complex problems.
Several different topics will be presented over the course of
the week. So far, the topics include
Statisticians on hand will come from UC Berkeley, UCLA, Stanford, UC Davis,
Rutgers University, Carnegie Mellon University, Bell Laboratories, and AT&T Labs.
- Bioinformatics and neuroscience
- Text and document analysis
- Environmental statistics
- Earth and space science
Importantly, students will also get a chance to work with
some of the data. In the process, students will gain a basic
understaning of computing and visualization tools.
Students will receive a grant to cover their travel expenses
to attend the workshop as well as full room and board at the Doubletree Hotel
in Westwood. Meetings will take
place in the Mathematical Sciences Building on the UCLA Campus.
Our short proram is geared toward undergraduates who are sophomores or
juniors in the 2005-2006 academic year.
They are expected to have some basic quantitative skills,
including a background in calculus. A
beginning course in probability and/or statistics would be helpful,
but is not required. Quantitatively-inclined undergraduates
majoring in engineering, computer
science, physics, biology, mathematics, statistics and the behavioral
or social sciences are all encouraged to apply. Given space constraints,
we can admit only 25 students.
Completed application forms are due April 21, 2006 and should include the following:
Forms can be submitted electronically to email@example.com. Please direct any questions about the program to this
email address as well.
- A completed application form
- A 1-2 page statement of interest
- A letter of recommendation from the instructor of a quantitatively-oriented course in which the student was enrolled
- A transcript (unofficial is acceptable)