Markov chains explained visually

In plain words

Markov Chains Explained Visually is an interactive educational tool that demonstrates how Markov chains work through visual demonstrations and examples. It's designed for students and anyone interested in understanding probability and stochastic processes. The resource uses animated graphics and interactive simulations to illustrate key concepts, making abstract mathematical ideas more concrete and accessible than traditional textbook explanations.

written from the facts on this page · September 2026

From the sources

Markov chains, named after Andrey Markov , are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the state space, a Markov chain tells you the probabilitiy of hopping, or "transitioning," from one state to any other state---e.g., the chance that a baby currently playing will fall asleep in the next five minutes without crying first. With two states (A and B) in our state space, there are 4…from setosa.io

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