Compute Markov steady state and expectations evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Answer the following probability/statistics sub-questions:
1) Given a finite-state, irreducible, aperiodic Markov chain with transition matrix P (provided), compute its stationary distribution π by solving πP = π with ∑i πi = 1, and state why the solution is unique.
2) Let X ~ Exponential(λ) and N ~ Poisson(λ), with λ > 0. Derive E[X] and E[N] from first principles (integration/summation), showing intermediate steps.
3) For a 2×2 zero-sum game with payoff matrix to Player A given in the prompt, find the mixed-strategy Nash equilibrium and report the probability each player assigns to their first action (use probability calculations to justify the equilibrium).
Quick Answer: Compute Markov steady state and expectations evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Context: The exact transition matrix P (for Q1) and the 2×2 payoff matrix (for Q3) are not provided. Below, you will (a) solve generically in symbolic form, and (b) see a small numeric example to illustrate the procedure.
Finite-state Markov chain
Given a finite-state, irreducible, aperiodic Markov chain with transition matrix P, compute its stationary distribution π by solving πP = π with ∑ᵢ πᵢ = 1. Explain why the solution is unique.
Expectations from first principles
Let X ~ Exponential(λ) and N ~ Poisson(λ) with λ > 0. Derive E[X] and E[N] from first principles (integration/summation), showing intermediate steps.
2×2 zero-sum game
For a 2×2 zero-sum game with Player A’s payoff matrix
[ [a, b], [c, d] ],
find the mixed-strategy Nash equilibrium. Report the probability each player assigns to their first action (row 1 for A, column 1 for B), and justify the equilibrium with probability calculations.
Clarifying Questions to Ask Guidance
Clarify the random variables, distributional assumptions, independence assumptions, and desired output.
Show enough derivation for the interviewer to follow the reasoning.
Explain how you would validate the result with simulation or sensitivity checks.
What a Strong Answer Covers Guidance
A correct setup with definitions, formulas, and boundary conditions.
A step-by-step derivation or estimation plan.
Interpretation of the result, including uncertainty and practical limitations.
Checks for assumptions, edge cases, and numerical stability.
Follow-up Questions Guidance
How would the result change if the assumptions were relaxed?
Can you verify the answer with a simulation?
What is the most likely source of estimation error?