Wednesday, 2 October 2013
As an ecologist, I'm used to conferences being a bit grim: audiences and presenters lament that there is no funding, extinction continues, and we don't really know what's going on. In contrast, the WA Young Statistician's Workshop was a rare treat of optimism and self-satisfaction. Triumphant, in demand, and beloved as nerds, data professionals are 'the new rock stars' and 'sexy' (according to conference attendees). Most of the attendeers were preoccupied with jobs and skill acquisition, but I found the following panel-question to be a noteworthy insights: what stats/math principles & techniques are under-realized now, but will have a huge windfall of applications in the future; or put another way, if there was a Noble Prize in Statistics, where would you place your bets today? Some answers: * finite-mixture models * techniques to deal with high-dimensionality * entropy under minimal constraints (mine) Other re-occurring themes were: * learn R; * R tops Python for data science, but Python is easier to learn has a lot to offer.