Abstract
Solomon Kullback (1907–1994) was born in Brooklyn, New York, USA, and graduated from the City College of New York in 1927, received an M.A. degree in mathematics in 1929, and completed a Ph.D. in mathematics from the George Washington University in 1934. Kully as he was known to all who knew him, had two major careers: one in the Defense Department (1930–1962) and the other in the Department of Statistics at George Washington University (1962–1972). He was chairman of the Statistics Department from 1964–1972. Much of his professional life was spent in the National Security Agency and most of his work during this time is still classified. Most of his studies on information theory were done during this time. Many of his results up to 1958 were published in his 1959 book, “Information Theory and Statistics.” Additional details on Kullback may be found in Greenhouse (1994) and Anonymous (1997).
When we receive something that decreases our uncertainty about the state of the world, it is called information. Information is like “news,” it informs. Information is not directly related to physical quantities. Information is not material and is not a form of energy, but it can be stored and communicated using material or energy means. It cannot be measured with instruments but can be defined in terms of a probability distribution. Information is a decrease in uncertainty.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
(2008). Information Theory and Entropy. In: Model Based Inference in the Life Sciences: A Primer on Evidence. Springer, New York, NY. https://doi.org/10.1007/978-0-387-74075-1_3
Download citation
DOI: https://doi.org/10.1007/978-0-387-74075-1_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-74073-7
Online ISBN: 978-0-387-74075-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)