Dear Nan and Randy Thanks for the descriptions you forwarded. Neither of these really seems to answer the question quantitatively, however. They don't say how to interpret the error. If I have a value X with an error Y, what can I do quantitatively with Y? If it's a standard error, and I assume that errors are normally distributed, I could infer there is a 95% chance that the true value is between X-2Y and X+2Y, for instance. That's because a standard error is an estimate of the standard deviation of values. Would you use the errors that you deal with like this? If so, we can call them standard errors. If not, how would you (or the users of your data) use them? If we knew that, we would be better able to decide how to describe them.
Best wishes Jonathan _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
