Your iPod Really Play Favorites?” rare characteristic that the culprit to highlight relationships between
They provide interesting ideas of a crime is known to possess is various distributions.
for classroom use in this article, guilty of the crime. In the final article, “A New Way
which was inspired by anecdotal Also in the Teacher’s Corner to Derive Locally Most Powerful
evidence of potential nonrandom section, Scott Lesch and Daniel Rank Tests,” Anthony Kuk
behavior of the shuffle feature. Jeske shine a light on lesser-known, explores a relationship between
Halvor Mehlum revisits a but accurate, approximations— derivatives of the log-likelihood
problem in forensic statistics in all based on the standard normal for observed data (the ranks) and
“The Island Problem Revisited.” distribution—of the Poisson and complete data (the underlying
Simplified, the island problem binomial cumulative distribution continuous variables). n
addresses the question of whether functions. They also point out how
a suspect who matches a known these approximations can be used
NISS to Work on Surveillance Project
The NISS project is one of 10 supported by NSF and
DTRA under a jointly funded program called Algorithms
for Threat Detection. Collaborative awards also were given
to Clemson University, the University of Georgia, and the
University of South Carolina. According to the Centers for
Disease Control and Prevention, syndromic surveillance uses
health-related data—such as hospital emergency room reports—
that precede diagnosis and signal a sufficient probability of a
case or outbreak to warrant further public health response. This
method also is used by public health officials to detect outbreaks
associated with natural causes or bioterrorism.
The research to be conducted will help DTRA develop
technology for controlling and reducing the threat from bio-
logical and chemical attacks. If a biological attack were made
in the United States, early detection would save millions of
lives. The results also will help with earlier detection of new
viruses. By identifying a virus such as avian flu or the next
strain of H1N1 early, health officials can help thwart the
onset of a pandemic.
Researchers also will look at intellectual issues such as scal-
ability, complex dependences in the data, covariates, temporal
T
he National Science Foundation (NSF) and Defense
and spatial variations, low-quality data, and how to minimize
Threat Reduction Agency (DTRA) have awarded
false positives.
$664,019 to the National Institute of Statistical
The principal investigators involved in the research include
Sciences (NISS) for collaborative research to develop Bayesian
Alan F. Karr, director of NISS; David Banks, professor of
methods for syndromic surveillance. The research focuses on
statistical science at Duke University; Gauri Datta, profes-
the use of conditionally auto regressive models to provide
sor of statistics at the University of Georgia; James Lynch,
quantified estimates of the probability that a disease is pres-
professor of statistics at the University of South Carolina; and
ent in a particular location, characterization of associated
Francisco Vera, assistant professor of mathematical sciences at
uncertainties, and computational implementation at a
Clemson University. n
nationwide scale.
20 AMsTAT NEWs OCTObER 2009
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