Noise consists of unwanted signals or signals that do not contribute to a message. It may be errors, random sound, or bits of other messages. It may even be "white noise" - the jumbled hum that is sometimes introduced into an environment such as a workplace to lower the level of distraction brought about by unaccustomed quiet or to muffle sudden sounds in an otherwise quiet area. What is "noise" and what is "information "depends very much on die purposes of the sender and the receiver. Even static on the radio could be information to someone in the vicinity who was interested in knowing when a power tool was turned on. Conversely, a report which consists primarily of raw data is very likely to be noise to a manager who receives it on a busy day. In this case it is not the content of the information which makes it noise but the form in which it is presented. The same may be true if an attempt is made to explain a situation to someone who does not share the same language or the same frame of reference. When there is more than one observer, the same distinction between what is noise and what is the message may not be made.
Redundancy is the means most often used to assure that a message is understood despite the SEE possibility of noise blocking part of the message or distortion due to error. Consider the difference if one character in “B4” or "before” is in error. The redundancy in the English language makes it unlikely that an error in the latter would lead to a misunderstanding of the message. Much important early work in information theory was done to determine how to send an accurate message over a noisy communication channel. Noise is likely to interfere in any actual communication channel, although it is possible to reduce it to an arbitrarily low level given sufficient resources. Shannon's Tenth Theorem deals with the required capacity of a correction channel required to correct a message to this arbitrarily low level. # SOURCE Shannon, C. E., & Weaver, W. (1964). The mathematical theory o f communication. Urbana: University of Illinois Press. # EXAMPLES • the static on the radio when you want to hear the news • a speech given to the wrong audience • any information; after the threshold of overload • data in a survey that responds to a coenetic variable rather than the topic of the survey • the conversation nearby that prevents you from hearing a presentation # NON-EXAMPLES • a message received and verified • a deliberate deception • a sound that you wish to hear # PROBABLE ERROR • Not recognizing all the factors that could make your message unintelligible to your intended receiver • mistaking noise for information # SEE Information; Channel Capacity; Redundancy; Complementarity; Filter