Information theory

Quantities of information

The mathematical theory of information is based on probability theory and statistics, and measures information with several quantities of information. The choice of logarithmic base in the following formulae determines the unit of information entropy that is used. The most common unit of information is the bit, or more correctly the shannon, based on the binary logarithm. Although "bit" is more frequently used in place of "shannon", its name is not distinguished from the bit as used in data-processing to refer to a binary value or stream regardless of its entropy (information content) Other units include the nat, based on the natural logarithm, and the hartley, based on the base 10 or common logarithm. In what follows, an expression of the form is considered by convention to be equal to zero whenever is zero. This is justified because for any logarithmic base. (Wikipedia).

Quantities of information
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Related pages

Symmetric function | Joint entropy | Mutual information | Statistics | Probability density function | Binary entropy function | Prior probability | Pearson's chi-squared test | Probability mass function | Information theory | Kullback–Leibler divergence | Likelihood-ratio test | Posterior probability | Conditional probability | Multinomial distribution | Probability distribution | Bit | Cross entropy | Expected value | Natural logarithm | Probability theory | Binary logarithm | Shannon (unit) | Nat (unit) | Conditional expectation | Conditional entropy | Common logarithm