31 March 2008
Here is a neat application of simulation from this weekend's New York Times. The authors, a graduate student and professor at Cornell, simulated the entire history of Major League Baseball 10,000 times to see just how "mythic" Joe DiMaggio’s 56-game hitting streak really is. They find that 56-game streaks are not at all unusual, and furthermore that Joe DiMaggio wasn't even the most likely to set the record!
For those who are interested in doing some simulations of their own, my guess is that the authors used the Lahman Baseball Database, which is freely available online. Perhaps in some future post I'll take a look at some simulations of other baseball records. Any suggestions for what to look at?
Please join us this Wednesday when Nicholas Christakis--Professor, Department of Sociology (Harvard University) and Medical Sociology (Harvard Medical School)--who will be present "Eat Drink and Be Merry: The Spread of Health Phenomena In Social Networks". Nicholas provided the following abstract:
Our work has involved the quantitative investigation of whether and how various health-related phenomena might spread from person to person. For example, we explored the nature and extent of person-to-person spread of obesity. We developed a densely interconnected network of 12,067 people assessed repeatedly from 1971 to 2003. We used longitudinal statistical models and network-scientific methods to examine whether weight gain in one person was associated with weight gain in friends, siblings, spouses, and neighbors. Discernible clusters of obese persons were present in the network at all time points, and the clusters extended three people deep. These clusters were not solely due to selective formation of social ties. A friend becoming obese in a given time interval increased a person's chances of becoming obese by 57% (95% CI: 6%-123%). Among pairs of adult siblings, one becoming obese increased the chance that the other became obese by 40% (21%-60%). Among spouses, one becoming obese increased the likelihood that the other became obese by 37% (7%-73%). Among those working in small firms, a co-worker becoming obese increased a person's chances of becoming obese by 41% (17-59%). Immediate neighbors did not exhibit these effects. We have also conducted similar investigations of other health behaviors, such as smoking, drinking, exercising, and the receipt of health screening, and of other health phenomena, such as happiness and depression. Various aspects of our findings suggest that the spread of social norms may partly underlie inter-personal health effects. Our findings have implications for clinical and public health interventions, and for cost-effectiveness assessments of preventive and therapeutic interventions. They also lay a new foundation for public health by providing a rationale for the claim that health is not just an individual, but also a collective, phenomenon.
Nicholas also provided a link to his paper here
The applied statistics workshop meets in room N354 in CGIS-Knafel, (1737 Cambridge st.) A light lunch will be served at 12 noon with the presentation beginning around 1215. Please contact me with any questions