Dear Readers,

In this issue, Stephen Fienberg puts the very notion of privacy in perspective: It would be more meaningful to elucidate privacy in conjunction with confidentiality and disclosure. Fienberg argues that the confidentiality pledge of the U.S. Census Bureau would, in fact, protect the privacy of individuals from harmful disclosure. On the contrary, when privacy policies of online social forums, such as Facebook, evolve into a labyrinth of lengthy legal documents, there is ample justification for the same individuals to be concerned about sharing their personal information with the rest of the world. According to Fienberg, the main challenge for the statistical community is to develop methods that contribute to the efficiency of policymaking through amassing data while guarding the privacy of the individual.

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Also, Roland Deutsch looks back at the 2010 World Cup in South Africa. Using the pre-tournament’s data obtained from the monthly rankings of FIFA, soccer’s primary international association, and three other well-regarded ranking systems, a nonlinear model is developed to calibrate the performance of the major contenders in the last World Cup. As for the U.S. national team, Deutsch paints a rosy portrait: That the Americans made it to the final 16, finishing at the top of their group ahead of England, is by itself a remarkable achievement.

Golf is a unique sport in its administration of a handicap system, allowing for two players with different skills to compete at the same predetermined level. James Lackritz demonstrates the fairness of this system using simulation studies, leading to a somewhat reassuring conclusion: The handicap system is indeed advantageous to the better players.

David Rockoff and Heike Hofmann look into the quality of visual judgments by analyzing a considerably large set of data from a web page devoted to a series of eyeballing games. There are two main inquiries of interest: what commonalities can be extracted from the patterns of performances of players who, regardless of the complexity of the games, consistently score higher—or lower—than the others and how statisticians can use these results to improve the accuracy of the graphical tools they employ for data analysis.

Tristan Barnett revisits the problem of optimal betting strategy in video poker. Conservative or aggressive game plans may well put the poker player at a disadvantage. However, there is a long-established betting benchmark, known as the Kelly criterion, for maximizing the player’s bank from one hand to the next. Barnett introduces us to two versions of this criterion for games having two and multiple outcomes. The criterion is used to calculate the expected profit of various hands in the all-American poker machine.

It has long been advocated that blackjack players familiar with card-counting systems would greatly profit from their skills. This assumption is put to the test by Bill Hurley and Andrey Pavlov through studying variations of the Hi-Lo counting system, popularized by Edward Thorp in his classic volume Beat the Dealer. Hurley and Pavlov, however, are not as optimistic as Thorp was: To guarantee success, a team of highly skilled and well-organized players is needed to bet large amounts of money over a long period of time.

As stated by Meena Doshi in Mark Glickman’s column, Here’s to Your Health, a significant portion of the U.S. population is affected by influenza every year. This leads to a considerable number of mortalities, and the costs of its socioeconomic aftermath adds to billions of dollars. There has been a number of statistical models for estimating mortality due to influenza, chief among which is Serfling’s seasonal regression. Doshi’s article highlights some of the major challenges associated with devising more sophisticated statistical tools for assessing the number of deaths due to disease.

In his column, Visual Revelations, Howard Wainer enlists a number of technical misnomers in the statistical nomenclature and suggests alternatives for them. Wainer opens his article, challenging the term “teacher effect,” as it is frequently used in value-added models.

Jonathan Berkowitz offers yet another exciting puzzle by paying tribute to the 125th anniversary of the publication of an iconic statistical work.

Finally, two announcements. First, it is my pleasure to introduce a new editor, Shane Reese from Brigham Young University. Second, Statistics Forum, the statistical blog sponsored by CHANCE and the American Statistical Association and edited by Andrew Gelman, is now up and running. In the short term since its inception, the forum has showcased articles by Michael Lavine, Howard Wainer, Christian Robert, and Andrew Gelman, among others. I urge readers of CHANCE to visit the forum.

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