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Curve Fit Stats




A question for both HS and college instructors. I've been looking at
some graphing and curve fitting packages, trying to figure out just
what statistics should be provided by the software when performing a
least-squares fit.

From my background, what's useful is the uncertainties on the fitted
parameters, ie, the standard error of the slope and intercept, or
whatever the parameters may be. That tells you how well determined
the slope is, for instance. The scatter standard deviation measures
how far away from the fitted line, on average, the points are. That's
useful too for comparison to the uncertainties of each y measurement.


However, many graphing packages, and all graphing calculators, only find
r or r^2, the correlation coefficient and coefficient of
determination, respectively. Now, these two numbers are related to
the probability that there is any correlation at all between the x and
y columns. Nothing more. That doesn't strike me as particularly
useful, as I already know there is a correlation--that's why I did
the experiment. I want to know the details of the correlation.

Does anyone out there actually use these r or r^2 numbers in curve
fits? How do your students interpret them?

What are the statistics that a good graphing package should give you?

My list is the following:

For a single column of numbers:

min
max
mean
std deviation
number of points
and optionally, std deviation of the mean

for a curve fit, be it linear or otherwise:

equation parameters (slope, intercept, etc)
std errors of parameters
scatter std deviation

The r and r^2 numbers don't play a role in any analysis that I
can think of in physics, so why bother students with them?

Again, my question:

Is there a use for r or r^2 statistics in college or hs physics
experiments? What?

Is there use of these commonly calculated values in chemistry or
bio?

JEG

John E. Gastineau
304 296 1966
Morgantown, WV
http://www.imagixx.net/~jgastin
email: jgastin@imagixx.net