An Interdisciplinary Journal

* 2011, Vol.14, No.2, pp.177-183*

Redundancy of experimental data is the basic statistic from which
the complexity of a natural phenomenon and the proper number of
experiments needed for its exploration can be estimated. The
redundancy is expressed by the entropy of information pertaining
to the probability density function of experimental variables.
Since the calculation of entropy is inconvenient due to
integration over a range of variables, an approximate expression
for redundancy is derived that includes only a sum over the set of
experimental data about these variables. The approximation makes
feasible an efficient estimation of the redundancy of data along
with the related experimental information and information cost
function. From the experimental information the complexity of the
phenomenon can be simply estimated, while the proper number of
experiments needed for its exploration can be determined from the
minimum of the cost function. The performance of the approximate
estimation of these statistics is demonstrated on two-dimensional
normally distributed random data.

*Key words: *
experimental information, information entropy,
redundancy, complexity

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Last updated: *September 28, 2011*