Foundations of Information Theory

This chapter explores the foundational concepts of information theory as introduced by Claude Shannon, emphasizing the quantification of information and the role of probabilities. It connects practical implications through relatable examples, such as coin flips and dice rolls, while discussing the complexity of communication with increased outcomes. The chapter further investigates the relationship between entropy in statistical mechanics and information theory, clarifying the dual use of the term 'entropy' and illustrating its relevance in understanding uncertainty.