The measure of uncertainty in a system of symbols is called:

Concept

In information theory, the uncertainty associated with a random variable or symbol source is quantified by Shannon entropy.

For symbol probabilities pi, its value is H(X) = -Σ pi log2 pi bits per symbol.

Application

The stem asks for the name of the quantity that measures uncertainty in a system of symbols. That information-theory quantity is entropy.

Contrast and cross-check

• Bandwidth describes an available frequency range or a channel capacity context; it does not name the probability-based quantity H(X).

• Loss describes attenuation, missing data, or reduced fidelity; it is not the distribution-based measure H(X).

• Quantum denotes a discrete unit in quantum theory; it is not the classical symbol-source measure H(X).

For n equally likely symbols, H(X) = log2 n, so uncertainty increases as the number of equally likely outcomes grows. For a certain symbol, H(X) = 0. This behavior confirms the uncertainty interpretation.

Therefore, the required term is entropy.