Back in the 1990s, British miners were fighting for compensation for diseases linked to coal dust exposure. Epidemiology and statistics were essential to the miners’ case, so mine operators sought to cast doubt on the data – and it fell to my father, Michael Jacobsen (pictured), to argue that the research was sound.
In 2012, the Harvard Business Review declared data scientist “the sexiest job of the 21st century”. Six years on it is still “America’s Hottest Job”, according to Bloomberg. As a statistician or data analyst you might be willing to give it a try. Of course, you need to know R. And both Modern Data Science with R (MDSR) and R for Data Science (R4DS) may help you find your way.
Our August 2018 cover story celebrates the 25th anniversary of the creation of R, the statistical programming language that became a subcultural phenomenon. While researching R’s history, community and culture, our reporter Nick Thieme interviewed a number of active R users and developers – and he invited them to tell our readers about some of the things they love most about R: specifically, the packages.
Poor practice is catching up with science,1-3 manifesting in part in the failure of results to be reproducible and replicable.4-7 Various causes have been posited,1, 8 but we believe that poor statistical education and practice are symptoms of and contributors to problems in science as a whole.
Fitbit, Garmin and other consumer heart-rate monitors are increasingly being used in clinical trials. The problem is, they’re not always very accurate.