# Stationary means

*From*: "Jason Foster" <retsofaj@xxxxxxxxx>*Date*: 3 Sep 2006 16:37:01 -0700

I don't think that this is a FAQ, but if it is I apologize for the

noise...

Discussions about "regression to the mean" tend to focus on fallacies

relating to heights, grades, sickness, etc. Something I have not seen

discussed is when/whether it is appropriate to assume a stationary mean

(or, I think alternatively, a fixed distribution)?

Assuming a constant distribution and repeated sampling, I can

intuitively understand regression to the mean. However, I can imagine

situations where the distribution is changing over time. For example

(and here I'm talking outside of my area of expertise) the mean height

in North America is increasing over time (ostensibly due to dietary and

health factors). If this is the case, then what would "regression to

the mean" mean? Towards which mean would the regression take place?

How would an observer know that a regression analysis is appropriate?

Any thoughts (or pointers to resources) on the issues would be

gratefully appreciated.

Jason

.

**Follow-Ups**:**Re: Stationary means***From:*dave

**Re: Stationary means***From:*Richard Ulrich

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