Doug wrote:
> Hi,
> 
> I was sitting through a presentation of some research yesterday about
> the results of a pilot study where a control group was compared with a
> treatment group and I found that I was rather confused about the use
> of the term standard error.  The researcher appeared to be saying
> something about having too small a standard error was not a good
> thing.

If you compute a statistic (such as a mean), the variability of that 
statistic is often expressed as the standard error of that statistic.

> Could someone please explain or link me to a page where I could get
> some detailed information about use of the standard error.  I think
> that it is a measure of the standard deviation of the sample means,
> but this doesn't appear to be the context that was used (from my
> understanding).

The term standard error can apply to statistics other than the mean.

> When is it good to have a large standard error?  When is it good to
> have a small standard error?  Do these answers differ for different
> tests and different experimental designs?

In some situations, a small standard error is not good. In most 
situations, a small standard error is good.

In comparing means, a small standard error is a good thing. If it 
gets really small, it can result in finding almost any two means to 
be significantly different. Some people think this is a bad thing, 
but it is not ... the problem is that people don't undesrtand that 
there is a difference between finding statistically significant 
differences and practically significant diffences. With very small 
standard errors, you may find means that are different by 0.01 to be 
significantly different, when in fact a subject matter expert may 
not think that differences less than a 1 are of any importance. 
(When this happens, it may indicate you have too large of a sample 
size, giving your test far more power than it needs)

A situation where a very small standard error may not be good is 
when you are fitting a model of some sort ... a very small standard 
error MAY indicate overfitting, which is not good ... but a very 
small standard error MAY ALSO indicate a very good model.

-- 
Paige Miller
Eastman Kodak Company
paige dot miller at kodak dot com
http://www.kodak.com

"It's nothing until I call it!" -- Bill Klem, NL Umpire
"When you get the choice to sit it out or dance, I hope you dance" 
-- Lee Ann Womack

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