  The modern practice of Radio Astronomy is characterized by extremes of data
volume and rates, principally because of the direct relationship between the
signal to noise ratio that can be achieved and the need to Nyquist sample the
RF bandwidth necessary by way of support. The transport of these data flows is
costly. By examining the statistical nature of typical data flows and applying
well known techniques from the field of Information Theory the following work
shows that lossless compression of typical radio astronomy data flows is in
theory possible. The key parameter in determining the degree of compression
possible is the standard deviation of the data. The practical application of
compression could prove beneficial in reducing the costs of data transport and
(arguably) storage for new generation instruments such as the Square Kilometer
Array.
