2026/2027.
35+ exam-style Q&A covering the key topics:
1 . Optimization: Variables, Constraints, Objective Function. Why integer programs take longer.
Linear regression objective = minimize squared error.
2. Probability & Distributions: Weibull, Exponential, Poisson. Memoryless property explained. k<l in
Weibull = failure rate decreases.
3. Simulation: Models that imitate real systems. Mixed/randomized strategies.
4. Machine Learning: Neural network process, layers, and K-Means clustering formula.
5. Time Series: Exponential smoothing S_t = ax_t + (1 -a)S_{t-1}. When a is close to 1.
6. Other: Design of Experiments, Approximate Dynamic Programming, Data imputation.
Clear, direct answers. No fluff. Perfect for fast review before Exam 3. Graded A+.
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EXAM 3.
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,Answer:
, ◍ what is the structure of markov decision processes.
Answer: stochastic dynamic program with discrete states and decisions; probabilities depend
only on current state/decision
◍ Another way to decrease the number of factors when doing multiple alternative of A/B testing.
Answer: Independent factors - test subset of combinations, use regression to estimate effects,
each factor is categorical variable
◍ AIC (Akaike Information Criterion).
Answer: 2k - 2ln(L*)L*: max likelihood valuek: number of parameters being estimated2k is
penalty term that balances likelihood with simplicity and avoids overfittingPrefer models with
smaller AICNice properties if there are inf many data points
◍ What are some downsides of surveys?.
Answer: Even if you have what appears to be a representative sample in simple ways, maybe it
isn't in more complex ways.
◍ what is the initial condition for T?.
Answer: T_1 = 0
◍ What are the three main components of the optimization models?.
Answer: variables, constraints, objective function ◍ what is an example
of a blocking factor.