entropy measures

Entropy measures the unpredictability or randomness within a system or dataset. In essence, it quantifies how much information is needed to describe the state of the system—higher entropy indicates greater disorder and less predictability, while lower entropy suggests more structure and predictability. For example, a well-organized bookshelf has low entropy, whereas a chaotic pile has high entropy. In information theory, it reflects the amount of surprise or uncertainty involved in predicting outcomes. Overall, entropy helps us understand the complexity and information content of systems across various disciplines.