There's a data deficit, and overcoming it leads to great personalization.
It generates a data deficit of 4 units, each couple counting as a symbol in the source alphabet.
H can equally indicate (a) or (b) because, by selecting a particular alphabet, the informer automatically creates a data deficit (uncertainty) in the informee, which then can be satisfied (resolved) in various degrees by the informant.
In the AB system, the occurrence of each symbol <_,_> removes a higher data deficit than the occurrence of a symbol in the A system.
A highly structured, perfectly organised message contains a lower degree of entropy or randomness, less information in Shannon sense, and hence it causes a smaller data deficit, which can be close to zero (remember the raven).
While unable to validate a relative data deficit for any physical disease, as we did for two types of psychopathology, the observed gaps are congruent with previously documented and variable healthcare utilization and access.
Before the coin is tossed, the informee (for example a computer) is in a state of data deficit greater than zero: the informee does not "know" which symbol the device will actually produce.
Adding an extra coin would produce a 8 units of data deficit, further increasing the amount of information carried by each symbol in the ABC system, and so on.
Current changes to the planning system(PDF), and calls to release more land to house a growing population, make this green belt data deficit all the more frustrating, particularly given the government claim that it 'attaches great importance to green belts' (National Planning Policy Framework, Chapter 9, p.19).
Equation [9] indicates that the quantity of information produced by a device corresponds to the amount of data deficit erased.
Equation [9] is Shannon's formula for H = uncertainty, which we have called data deficit (actually, Shannon's original formula includes a positive constant K which amounts to a choice of a unit of measure, bits in our case; apparently, Shannon used the letter H because of R.V.L. Hartley's previous work).
