4,582 research outputs found
Brief history of the Lehmann Symposia: Origins, goals and motivation
Full text linkThe idea of the Lehmann Symposia as platforms to encourage a revival of
interest in fundamental questions in theoretical statistics, while keeping in
focus issues that arise in contemporary interdisciplinary cutting-edge
scientific problems, developed during a conversation that I had with Victor
Perez Abreu during one of my visits to Centro de Investigaci\'{o}n en
Matem\'{a}ticas (CIMAT) in Guanajuato, Mexico. Our goal was and has been to
showcase relevant theoretical work to encourage young researchers and students
to engage in such work. The First Lehmann Symposium on Optimality took place in
May of 2002 at Centro de Investigaci\'{o}n en Matem\'{a}ticas in Guanajuato,
Mexico. A brief account of the Symposium has appeared in Vol. 44 of the
Institute of Mathematical Statistics series of Lecture Notes and Monographs.
The volume also contains several works presented during the First Lehmann
Symposium. All papers were refereed. The program and a picture of the
participants can be found on-line at the website
http://www.stat.rice.edu/lehmann/lst-Lehmann.html.Comment: Published at http://dx.doi.org/10.1214/074921706000000347 in the IMS
Lecture Notes--Monograph Series
(http://www.imstat.org/publications/lecnotes.htm) by the Institute of
Mathematical Statistics (http://www.imstat.org
SurveyMan: Programming and Automatically Debugging Surveys
Full text linkSurveys can be viewed as programs, complete with logic, control flow, and
bugs. Word choice or the order in which questions are asked can unintentionally
bias responses. Vague, confusing, or intrusive questions can cause respondents
to abandon a survey. Surveys can also have runtime errors: inattentive
respondents can taint results. This effect is especially problematic when
deploying surveys in uncontrolled settings, such as on the web or via
crowdsourcing platforms. Because the results of surveys drive business
decisions and inform scientific conclusions, it is crucial to make sure they
are correct.
We present SurveyMan, a system for designing, deploying, and automatically
debugging surveys. Survey authors write their surveys in a lightweight
domain-specific language aimed at end users. SurveyMan statically analyzes the
survey to provide feedback to survey authors before deployment. It then
compiles the survey into JavaScript and deploys it either to the web or a
crowdsourcing platform. SurveyMan's dynamic analyses automatically find survey
bugs, and control for the quality of responses. We evaluate SurveyMan's
algorithms analytically and empirically, demonstrating its effectiveness with
case studies of social science surveys conducted via Amazon's Mechanical Turk.Comment: Submitted version; accepted to OOPSLA 201
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