• The first ‘so-called’ communication theory
• Widely cited in my disciplines
• Introduced basic terminology
• Foundation for other theories

Information
The amount of uncertainty a message eliminates
      =
Opportunity to Reduce Uncertainty
      =
Reducing Entropy
A measure of the degree or randomness, chaos,
and disorde
 

NOISE
Definition: Noise is anything added to
the signal that’s not intended by
the source.
Purpose: Noise reduces information by
increasing uncertainty.
Question: What are some examples of noise?

REDUNDANCY
Definition: Predictability or repetition
of the message.
Purpose: Reduces loss of information
due to noise.
Question: Where does redundancy fall on the linear model

Norbert Weiner’s concept of  FEEDBACK
Definition: A method of adjusting future
action by analysis of past performance
Purpose: Feedback adds the concept of
learning to information theory.
Question: Where does feedback fall on the linear model

Application Questions

• Is communication like a modem?
• When we try to communicate with someone else are we often trying to send a message to reduce someone’s uncertainty?
• Is information (reduction or uncertainty) the most important value of communication?
• Does this model help us in our everyday lives?