Markov Chain: Weather Toy Model
This interactive simulator explores Markov Chain (Weather) in Math Visualization. Sun/Rain two-state chain: P matrix, stationary π, empirical vs theory. Use the controls to change the scenario; watch the visualization and any graphs or readouts to connect the model with lectures, labs, and homework.
Who it's for: Suited to beginners and first exposure to the topic. Typical context: Math Visualization.
Key terms
- markov
- chain
- weather
- markov chain weather
- math
- visualization
How it works
A minimal Markov model for teaching: memoryless transitions, stationary distribution, and convergence of time averages.
More from Math Visualization
Other simulators in this category — or see all 26.
Gradient Descent (2D)
Level sets of f(x,y) and path (x,y) ← (x,y) − η∇f; bowl or elliptic well.
Minkowski Diagram
Light cone and boosted axes in 1+1D; γ from v.
Twin Paradox
Out-and-back worldlines; proper time τ = T/γ vs Earth time T.
Monte Carlo π
Uniform samples in a square; 4·(in disk)/N estimates π.
Random Walk
1D or 2D steps; trail and running mean ⟨r²⟩ vs diffusion intuition.
Vector Addition
Place vectors and see the resultant with head-to-tail animation.