American Statistical Association
Many, if not most statistical methods implicitly or explicitly depend on assumptions about the underlying distribution of the observations, assume asymptotic or approximate distributions, or are optimal (most accurate, most efficient, etc.) for particular types of distributions. Through heuristics, empirics and graphical display, we will explore the what, why and how of using transformations to bring data, real and simulated, closer to those assumptions. We can thus reduce the mathematics needed for mathematical statistics.
|Date:||Wednesday, February 7, 2007|
|Time:||4:00 P.M. - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.