Here's an example of what I mean by "model-free" in the context of confidence interval calculations: http://www.analyticbridge.com/profiles/blogs/how-to-build-simple-accurate-data-driven-model-free-confidence-in > Vincent Granville asked 16 March 2012 00:40: "should general linear models > (for statistical inference) still be taught? Shouldn't the curriculum > focus on sophisticated computer-intensive simulations ... The advantages > are: ... model-free, non parametric approach, applies to any type of > data" > > My bugbear is the confusion created by the phrase "general linear model", > promoted by eg SAS, which is a limited subset of "generalized linear > models". The latter *should* be taught. The suggestion that simulations > are model-free and non-parametric (ie distribution free) is irrational. > How can you run a simulation without a model based on distributions? > > Allan > This email and any attachments are intended for the named recipient only. > Its unauthorised use, distribution, disclosure, storage or copying is not > permitted. > If you have received it in error, please destroy all copies and notify the > sender. In messages of a non-business nature, the views and opinions > expressed are the author's own > and do not necessarily reflect those of Cefas. > Communications on Cefas’ computer systems may be monitored and/or > recorded to secure the effective operation of the system and for other > lawful purposes. > -- Vincent Granville, Ph.D. Executive Director, Founder www.analyticbridge.com [log in to unmask] 925-759-7308 (cell) 425-837-4767 (office) You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.