John guided us through data collected by the Freeway Performance Measurement System (PeMS), a real-time monitoring system tracking flows of traffic in California. We explored the relationship between flow (a measure of "throughput" of the freeway system) and occupancy (a measure of congestion) and how these vary over time, across lanes, and in response to "events." We also looked at forecasting travel times and evaluated predictions for trips with different start times.

Using data from the PeMS web site we finished the day with some questions:

We worked in groups of three and presented our analyses; some groups worked in R, others preferred ggobi displays.

The day started with a short lecture from Terry to define some terms; a Single Nucleotide Polymorphism (SNP) is a variant form of DNA at a well-defined position on a chromosome. Researchers are genotyping thousands of individuals at thousands of SNPs, in the hope of finding associations between SNP genotypes and disease with genetic components, and other genetic traits. While there are many ways to determine a person's genotype at an SNP, our data came from an Affymetrix SNP chip. We looked at data for one SNP. Terry provided us with a data frame consisting of Affymetrix probe intensities for 90 individuals; for each person in the study, we were given intensities for 40 probes.

We ended the day with an open discussion by five statistics graduate students: Neda Farzinnia, Katie Tranbarger, Jae Brodsky, Soyeon Ahn and Frances Tong. We had lots of questions about the difference between life as an undergraduate versus that of a graduate, the process of selecting an advisor, and student "community."

The signal from wireless devices like PDA's and mobile phones can be picked up by various fixed receivers or access points. If you are near an access point, the (received) signal strength is large; if you are distant, it is small. Diane posed a simple question: Can measurements of signal strength at various wireless access points be used to identify a person's location? She brought a data set of signal strengths recorded at a handful of access points as a researcher roamed the corridors of one floor of an office building.

By this point in the program, we had enough experience with R to explore the data in a very open-ended way. Some groups created plots of signal strength, overlaying these measurements onto a map of the building, while others looked at the relationship between signal strength and distance to the access points. Time flew by on these projects; we were so absorbed that it was tough to break for lunch! Today, Jan de Leeuw, Chair of the UCLA Statistics Department, joined us for lunch at the faculty center. After lunch, we returned to work, ultimately presenting our findings through a series of group presentations.

Doug Nychka, National Center for Atmospheric Research

In addition to Doug, we were joined by David James, a researcher from Bell Laboratories. Our project dealt with extreme precipitation events. The frequency of large amounts of rainfall is important for planning for floods and effects how land and roadways should be developed. Doug provided us with climatic data from 56 weather stations located along Colorado's Front Range (FR).

The FR consists of relative flat plains with a transition to high mountains. Because of this diversity it is useful study area to test methods. The variable of interest is the total amount of precipitation in a 24 hour period during the "summer." Doug guided us through the following questions:

Next, we took a quick field trip to Bill Kaiser's lab; Bill is part of the CENS group and works with robotic data collection devices.

Computer Vision
Yingnian Wu, UCLA

This was the last day of our program, and it was divided into two sections. In the first, Yingnian gave us a basic introduction to some of the problems in computer vision. We learned about R's capabilities for working with image data, and applied some simple filters to digital photographs taken from the first five days of our workshop. Yingnian then described some basic statistical properties of natural images, including so-called "scaling" behavior (what happens as you zoom in and out of a scene).

After lunch, we had a series of presentations. Some students spoke in groups, others flew solo. In each case, they were asked to dig a little deeper into some of the data they had seen during the week and talk about "analysis" that they found particularly satisfying. For some, this was a plot that they were proud of, while for others it was an investigation, a thought process, that led them to some interesting conclusions.