The American Statistician
Voting Leads February Issue
Peter Westfall, The American Statistician Editor
A
special section of TAS called
Statistics for Democratic
Processes leads the February
issue with a series of three articles.
“Predicting Presidential and Other
Multistage Election Outcomes
Using State-Level Pre-Election
Polls” is presented by William F.
Christensen and Lindsay W. Florence.
A paper about election auditing follows by
Mary Batcher, John McCarthy, Howard Stanislevic, Mark
Lindeman, Arlene S. Ash, and Vittorio Addona that shows flaws in
recent legislation for percentage-based audits. Related to auditing
election results is a paper about estimating the number of valid signa-
tures on a petition by Mary M. Whiteside and Mark E. Eakin.
For our Statistical Practice section, Russell A. Boyles argues that
one-sided intervals are bad statistical practice, as they violate the
“law of likelihood.” David Afshartous then provides perspectives
as a statistician in a legal case where sample size determination for
the binomial p was a key element.
We have a special treat in Teachers’ Corner. Lawrence M.
Approximate sampling distribution for “Bush electoral votes” using the
weighted-polls data assimilation method on November 2, 2004. From
Leemis and Jacquelyn T. McQueston provide a graphic that shows
“Predicting Presidential and Other Multistage Election Outcomes Using
relationships between various probability distributions, greatly
State-Level Pre-Election Polls” by William F. Christensen and Lindsay
updating Leemis’ popular paper, “Relationships Among Common
W. Florence.
Univariate Distributions.” The issue comes with a pull-out of the
graphic, perfect for posting on a classroom wall. slant and Taylor and Chicon’s book to those wishing to emphasize
Following this paper is one about assessment, a topic on every- the collection and presentation of data. He suggests Lee’s book for
one’s minds these days, especially with pressure from accrediting a supplemental honors or graduate text.
agencies. Contributions by Mark L. Berenson, Jessica Utts, Karen Next, Xiaogang Su calls Data Mining Methods and Models by
A. Kinard, Deborah J. Rumsey, Albyn Jones, and Leonard M. Daniel T. Larose appropriate for an introductory, graduate-level
Gaines are included. Finally, Michael A. Proschan gives a fresh and course on data mining in which students come from varied back-
intriguing look at the normal approximation to the binomial. grounds. Phil Wood nixes Confirmatory Factor Analysis for Applied
History Corner marks the centennial of the publication of Research by Timothy A. Brown. Charles L. Liss then reviews Study
Gosset’s original “Student t” paper with a paper by James A. Hanley, Design and Statistical Analysis: A Practical Guide for Clinicians and
Marilyse Julien, and Erica E. M. Moody, titled “Student’s z, t, and Multivariable Analysis: A Practical Guide for Clinicians, 2nd ed.,
s: What if Gosset Had R?” Herbert A. David provides a nice coun- both by Mitchell H. Katz, in tandem, calling them useful intro-
terpoint with his paper, “The Beginnings of Randomization Tests.” ductions for novice investigators. Gregory Gilbert thinks A Pocket
The General section contains a paper about confidence intervals Guide to Epidemiology by David G. Kleinbaum, Kevin M. Sullivan,
for a discrete population median by Denis Larocque and Ronald and Nancy D. Barker has excellent topical content, but suffers from
H. Randles and one by Frank Tuyl, Richard Gerlach, and Kerrie poor presentation.
Mengerson comparing various priors for the binomial p in the case The section closes with brief mentions of (reviewers in parenthe-
where there are zero successes. ses) Applied Regression Analysis and Other Multivariable Methods, 4th
Reviews reports on 11 books. Richard J. Cleary opens with a ed., by David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam,
tandem review of three books designed to teach introductory statis- and Keith E. Muller (Christine M. Anderson-Cook); Data Analysis
tics from atypical perspectives: Bayesian Statistics: An Introduction, and Graphics Using R: An Example-Based Approach, 2nd ed ., by
3rd ed., by Peter M. Lee; Fundamentals of Probability and Statistics John Maindonald and John Braun (Christine M. Anderson-Cook);
for Engineers by T. T. Soong; and Statistical Techniques for Data and SPSS for Introductory Statistics: Use and Interpretation, 3rd ed.,
Analysis, 2nd ed., by John K. Taylor and Cheryl Cihon. Cleary by George A. Morgan, Nancy L. Leech, Gene W. Gloeckner, and
recommends Soong’s book to those seeking a heavily mathematical Karen C. Barrett (Amy Herrin). ■
10 AMSTAT NEWS FEBRUARY 2008
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