By National Research Council, Computer Science and Telecommunications Board, NII 2000 Steering Committee
Because the number of all private and non-private info prone. yet how and whilst will the NII turn into a fact? How will extra and higher companies succeed in the house, small company, and distant destinations? This publication examines those and different questions.
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The preelection process reduced this entropy to nearly 1 bit (characterizing the nearly equally likely success of Carter and Ford before election day on which voters removed the remaining uncertainty). Finally, entropy is also the key to a fundamental law in the cybernetics of regulation. Ashby's (1956) law of requisite variety, which states that "only variety can destroy variety," implies that the survival of a system depends on its ability to generate at least as much variety within its boundaries as exists in the form of threatening disturbances from its environment.
Part of the definition of entropy, and one reason for calling it a measure of observational variety, is that unobserved possibilities do not enter the measure. The average is computed only for categories of observations that do occur at least once. This is reflected in the convention adopted here: 0log20 = 0. Note some of its properties. Entropies are zero or positive and limited by Page 17 where NA is the number of categories in variable A and n is the sample size. The entropy is zero when observational variety is absentthat is, when distinctions are vacuous and all observations are of the same kind, pa = 1 for one category and zero for all others, in which case both 1log21 = 0 and by convention 0log20 = 0.
This places information theory into a framework that most social scientists can readily comprehend and evaluate. Professor Krippendorff's thorough understanding of the theory and use of information theory also takes the careful reader a long way toward competency. This book is particularly successful at making a rather complicated system for analyzing multivariate qualitative data as simple as possible. Krippendorff does this by building the entire presentation around intuitively appealing notions of information, such as the amount of information provided by an answer to a question, the amount transmitted through a noisy channel, and so on, rather than by using the axioms and theorems of information theory.