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TAS Highlights
Statisticians: Desired and Feared
John stufken, TAS Editor
w
ith an ever-increasing identify sufficient conditions that
demand for statistics, will lead to this paradox and pro-
we are desired. But vide a link to Simpson’s Paradox.
with lingering uneasiness about On cue, Marios Pavlides and
our methods and concepts, we Michael Perlman entertain
also are feared. Xiao-Li Meng the question, “How Likely Is
discusses challenges for our cur- Simpson’s Paradox?” Variations of
ricula that stem from this new this question are answered, either
status in the thought-provoking exactly or through simulation. For
lead article, “Desired and example, in a 2 x 2 x 2 contingen-
Feared—what Do we Do Now cy table, if the cell probabilities
and Over the Next 50 Years?” are distributed uniformly over
Naturally, being desired also gives the entire probability simplex,
rise to tremendous opportunities Simpson’s Paradox occurs with
for the discipline, and the ques- probability 1/60.
tion is whether we can take The article “Uniformly Hyper-
advantage of this. By discussing Efficient Bayes Inference in a
recent developments at Harvard Class of Nonregular Problems,”
University, Meng rallies the by Daniel Nordman, Stephen
troops with an emphatic “Yes Vardeman, and Melissa
We Can.” Bingham, presents an interesting
and unusual class of nonregular
General
continuous statistical models,
Statistical Practice
In the General section, Micha
where ordinary maximum likeli-
Mandel and Yosef Rinott present
hood is not available, but Bayes
The Statistical Practice section
an interesting study on inference
methods are hyper-efficient and
opens with “A Statistical Problem
in the presence of selection bias.
achieve convergence rates far in
Concerning the Mar Saba Letter,”
If, for example, in studying the
excess of the usual n-1/2 uniform-
by Andrew Solow and Woolcott
toxicity of a drug, only successful
ly across the parameter space.
Smith. This letter was purport-
studies are published, how should
Arne Bathke, Oliver
edly written by a second-century
we perform inferences about the
Schabenberger, Randall Tobias,
theologian, but there is evidence
drug’s toxicity based on only the
and Laurence Madden exhibit
that it is a forgery. The authors
published results? Does the fre-
and explore a relationship between
provide a statistical framework
quentist paradigm provide a more
the Greenhouse-Geisser F adjust-
for studying the letter’s authentic-
satisfactory approach than the
ment and an ANOVA-type statis-
ity. Per Gösta Andersson follows
Bayesian paradigm, or vice versa?
tic in nonparametric inference for
this with an interesting article
In “A Selection Bias Conflict
factorial designs in their article,
that provides a simple method
and Frequentist versus Bayesian
“Greenhouse-Geisser Adjustment
for adjusted confidence intervals
Viewpoints,” the authors explore
and the ANOVA-Type Statistic:
when a point estimator and an
these and related questions.
Cousins or Twins?”
estimator of its variance are sub-
The next two articles in this
In the final article of this
stantially correlated.
section focus on paradoxes. Aiyou
section, Carl Morris and Kari
Teacher’s Corner
Chen, Thomas Bengtsson, and
Lock unify the six univariate
Tin Kam Ho revisit the “regres-
natural exponential families with
In Teacher’s Corner, Amy
sion paradox,” where counterintu-
quadratic variance functions,
Froelich, William Duckworth,
itive conclusions appear to result
exhibiting relationships between
and Jessica Culhane investigate
from considering a direct and
these families and with other
the randomness of the shuffle
reversed linear regression. They
common distributions.
feature on the iPod in “Does
OCTObER 2009 AMsTAT NEWs 19
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