Markov chain
Understand the Problem
The question is simply asking for information about Markov chains, which are mathematical systems that undergo transitions from one state to another, within a finite or countable number of possible states. This concept is commonly used in various fields such as statistics, machine learning, and physics.
Answer
A Markov chain is a stochastic process where each event's probability is based solely on the previous event.
A Markov chain is a stochastic model describing a sequence of events where the probability of each event depends only on the previous event.
Answer for screen readers
A Markov chain is a stochastic model describing a sequence of events where the probability of each event depends only on the previous event.
More Information
Named after the Russian mathematician Andrey Markov, Markov chains are used in various fields such as finance, game theory, algorithm analysis, and others, for modeling random processes in systems that progress through states.
Tips
A common mistake is to assume that future probabilities depend on more than just the current state. It is essential to remember that Markov chains rely purely on the present state for probabilistic predictions.
Sources
- Markov chain - Wikipedia - en.wikipedia.org
- Markov Chains | Brilliant Math & Science Wiki - brilliant.org
- Markov Chain Explained | Built In - builtin.com
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