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Re: axes labels on errorbar plots


From: Przemek Klosowski
Subject: Re: axes labels on errorbar plots
Date: Mon, 24 Nov 2003 14:45:34 -0500 (EST)

    przeme >numerical and measurement error should be treated the same; I think
    przeme >the fundamental principle is that there are two sources of error:

    Yeah, I'd say that the three are distinct:

    *     error due to inexact representation floating-point numbers.
    *     error due to the finite resolution of any real-world measurement
         ( i.e., significant figures, & error range ).
    *      error due to calculation via an inexact (vs. exact) method.

why do you think that inexact representation has to be treated
differently than measurement error? They both can be described by
confidence intervals. True, they have different probability
distribution: hardbox like for truncation (x IS between
x_with_truncated_LSB and x_with_set_LSB) and gaussian for your typical
error, with 68.26% probability that x is within x-sigma and
x+sigma. However, if you start playing those games, why not
distinguish between different statistical distributions of measurement
error: what if you have an experimental variable with Poisson
statistics, instead of Gaussian?

I am comfortable with describing all errors in the same way, as
confidence intervals. If you need a confidence higher than 68%, you
can widen your interval (+- 2 sigma will give you 95% confidence,
etc).  The Central Limit Theorem says that almost always you quickly
get into Gaussian distribution region, anyway, so if you start with
certain confidence level, your confidence intervals proceed to be at
this level.



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