Markov Chain

An interactive experiment that visually demonstrates how randomness stabilizes over time. Two coins are flipped repeatedly - Coin A is perfectly fair (50/50), while Coin B secretly carries a hidden bias. As the number of trials increases, the running percentages reveal statistical drift, noise smoothing, and eventual convergence toward the true underlying probabilities. Includes live stats, inference engine, auto-flip, and real-time probability graphing.

This visualization represents a first-order Markov chain built from the sample text. Each node is a word, and each directed arrow shows the probability that one word follows another in the source text. Thicker lines and higher numeric probabilities indicate more frequent transitions. Type into the input box to receive live Markov-based next-word predictions, enabling a primitive autocomplete system derived directly from the training text.