Faculty use

Markov Chains and Stationary Distributions

Reward correct mathematics, explicit dimensions/hypotheses, interpretation, and verification. Equivalent valid reasoning should receive credit.

Problem 1

Each column sums to 1, so it is column-stochastic.

Problem 2

A probability vector π unchanged by the transition: Pπ=π.

Problem 3

Definitions should identify the vector/matrix/space/transformation, dimensions or domain/codomain, and the hypotheses behind modelling probability transitions and long-run behavior. Use the formulas x_{k+1}=Px_k; Pπ=π.

Problem 4

A strong error analysis identifies the first step that violates a definition, dimension, theorem hypothesis, or matrix-operation rule; then repairs that step and re-verifies the final result.

Problem 5

Application responses vary. Require defined variables, a compatible matrix/vector model connected to population movement, networks, computer graphics, communications, search, recommendation, and dynamic systems, a complete computation, interpretation, and limitations.

Problem 6

Accept two independent checks appropriate to the task: reconstruction, residual, RREF comparison, determinant/rank test, orthogonality, substitution, eigenpair check Av=λv, factorization product, or a second method.

Scoring guidance

Six problems × 10 points: 5 mathematical accuracy, 2 structure/justification, 2 verification/interpretation, 1 notation and communication.

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