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Undergraduate · Two-state Markov chains · 110 of 650

Two-state Markov chains · Transition 1 → 2: p=0.5; Transition 2 → 1: q=0.6

Use n=7 transitions. Find the probability of state 1, its stationary probability, and the signed convergence multiplier. Givens: Transition 1 → 2: p=0.5; Transition 2 → 1: q=0.6.

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01 · Make a prediction

Your practice question

A two-state chain has row transition matrix [[0.5,0.5],[0.6,0.4]] and starts entirely in state 1. Use n=7 transitions. Find the probability of state 1, its stationary probability, and the signed convergence multiplier.

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02 · Explore the model

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Watch the relationship

Paused
Two-state Markov chains · Transition 1 → 2: p=0.5; Transition 2 → 1: q=0.6. Step: 0. State-one probability: 1. Stationary probability: 0.545. Error multiplier: -0.1Probabilities approach stationary balance010612probability of state 1step n → · labeled axes rescale to this model
The row-stochastic transition matrix is [[1−p,p],[q,1−q]], with both probabilities strictly between zero and one. The initial distribution is (1,0). These are exact distribution updates, not simulated individual trajectories.

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Make it your experiment

Change one value. Notice what follows.

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Step
0
State-one probability
1
Stationary probability
0.545
Error multiplier
-0.1

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From experiment to screen.

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The mathematical idea

A distribution can settle into a stationary balance while individuals continue changing state. Starting entirely in state one, the distance from stationarity is multiplied by 1−p−q each step. A negative multiplier causes alternating approaches without making any probability negative. A two-state chain has row transition matrix [[0.5,0.5],[0.6,0.4]] and starts entirely in state 1. Use n=7 transitions. The requested state occurs at 60% playback; use the exact target stated in the question for your calculation.

π₁=q/(p+q); Pₙ(1)=π₁+(1−π₁)(1−p−q)ⁿ

03 · Reflect and transfer

Explain what changes and why.

What happens when p+q=1, and why does that special case reach the stationary distribution after one update?

This is a distinct guided scenario using a reusable mathematical model. Similar-looking diagrams can represent different given values and conclusions; they are not different mathematical theories.