On Feb 20, 2011, at 1:27 PM, Ben Ward wrote:
However, the
Y ~ X + Y^2
Produces the best fitting line - it is pretty much on the data
points - I'm trying to make a standard curve, with which to take
readings from a spectrophotometer off of. Rather than what I would
normally use models for - such as hypothesis testing and analysis of
data from experiments.
I thought we were leaving behind the model that had the dependent
variable on both sides of hte equation. Can you explain how you would
construct a chart or a function that will turn those results into
something useful?
Thanks,
Ben.
On 20/02/2011 11:53, nzcoops wrote:
model<- lm(Approximate.Counts~X..Light.Transmission +
I(Approximate.Counts^2), data=Standards)
Might not be addressing the problem, don't you have Y ~ X + Y^2
here? That's
a violation of the assumptions of an lm isn't it?
Also for plotting CI on a curve look into ggplot2::geom_ribbon,
it's much
nicer than just plotting lines and is easy to use. had.co.nz should
set you
right for setting this up.
David Winsemius, MD
West Hartford, CT
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