Speaker: Keith O’Rourke – Ottawa, Ontario
Title: Can we get a mathematical framework for applying statistics that better facilitates communication with non-statisticians as well as helps statisticians avoid getting “precise answers to the wrong questions*”?
Date: Friday, March, 6, 2015
Time: 1:30-2:30 p.m.
Place: HP 4351 (Macphail room), Carleton University
Abstract: Applying statistics involves communicating with non-statisticians so that we grasp their applied problems and they understand how the methods we propose address our (incomplete) grasp of their problems. Statistical theory on the other hand, involves communicating with oneself and other qualified statisticians about statistical models that embody theoretical abstractions and one would be foolish to limit mathematical approaches in this task. However, as put in Kass, R. (2011), Statistical Inference: The Big Picture – “Statistical procedures are abstractly defined in terms of mathematics but are used, in conjunction with scientific models and methods, to explain observable phenomena. … When we use a statistical model to make a statistical inference [address applied problems] we implicitly assert … the theoretical world corresponds reasonably well to the real world.” Drawing on clever constructions by Francis Galton and insights into science and mathematical reasoning by C.S. Pierce, this talk will discuss an arguably mathematical framework (in the Peirce’s sense of diagrammatic reasoning) that might be better. * “An approximate answer to the right question is worth a great deal more than a precise answer to the wrong question.” – John Tukey.