Shannon Entropy Calculator

Calculates the Shannon entropy for a given set of data, providing a quantitative measure of uncertainty or randomness within the information contained in that dataset. The tool accepts probability distributions as input and computes the entropy value using the standard formula, which measures how much "surprise" is associated with the outcomes. Understanding this metric helps users quantify the predictability of a source; higher entropy indicates greater unpredictability, while lower values suggest the data tends to follow predictable patterns or limited outcomes. Researchers in fields such as information theory, machine learning, and bioinformatics utilize this calculator to analyze complex systems and model sources of randomness. It assists students and practitioners who need to determine the informational content or diversity inherent in a discrete set of probabilities.