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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
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Vincent Granville, Ph.D.
Executive Director, Founder
www.analyticbridge.com
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