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S.E. Fienberg 149computed the area under the curve for each study, A, rank-ordered the valuesof A, and then used symmetric ROC curves corresponding to the quartiles forthese values. These curves also happen to enclose approximately 50% of thedata points as well.) The committee chose this scatterplot, which includes essentiallyall of the relevant data on accuracy from the 52 studies, rather than asingle summary statistic or one with added standard error bounds because wejudged it important to make the variability in results visible, and because ourinternal analyses of the characteristics of the studies left us suspicious that thevariability was non-random. Polygraph accuracy likely depends on unknownspecifics of the test situation, and we did not want to create the impressionthat there is a single number to describe polygraph accuracy appropriatelyacross situations.Although I thought this was going to be a one-of-a-kind activity, I guessI should have known better. About a year after the release of the report,I testified at a senate hearing on the Department of Energy’s polygraph policy(Fienberg and Stern, 2005), and continue to be called upon by the mediato comment on the accuracy of such methods for the detection of deception— as recently as this month, over 10 years after the publication of our report.13.8 Take-home messagesWhat are the lessons you might leave this chapter having learned?(a) First, it’s fun to be a statistician, especially because we can ply our sciencein a diverse set of ways. But perhaps most of you already knew that.(b) Second, big problems, especially those confronting the nation, almost alwayshave a statistical component and working on these can be rewarding,both personally and professionally. Your work can make a difference.(c) Third, working on even small aspects of these large national problemscan stimulate the creation of new statistical methodology and even theory.Thus if you engage in such activities, you will still have a chance to publishin the best journals of our field.(d) Fourth, such new methods often have unplanned-for applications in otherfields. This will let you, as a statistician, cross substantive boundaries innew and exciting ways.Who would have thought that working on a few problems coming out of theHalothane Study would lead to a new integrated set of models and methodsthat would have impact in many fields and in different forms?