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ISYE 6644 Midterm Actual Exam – Newest Questions Simulation and Modeling for Engineering and Science – Georgia Tech

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ISYE 6644 Midterm Actual Exam – Newest Questions Simulation and Modeling for Engineering and Science – Georgia Tech

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ISYE 6644 Midterm Actual Exam – Newest Questions
Simulation and Modeling for Engineering and Science –
Georgia Tech


EXAM OVERVIEW & KEY STUDY AREAS

Aspect Details

Course ISYE 6644 – Simulation and Modeling for Engineering and Science

Institution Georgia Institute of Technology

Exam Coverage Modules 1-7 (Midterm 1 & 2 content)

Weight ~2/3 theory (probability/statistics) + ~1/3 programming (Arena)



SECTION 1: SIMULATION FUNDAMENTALS & HISTORY (Questions 1-15)

Q1. What is a model in the context of simulation?

A) A exact replica of a real-world system
B) A high-level representation of the operation of a real-world process or system
C) A mathematical equation that predicts all outcomes
D) A physical scale model of a system

Correct Answer: B. A high-level representation of the operation of a real-world
process or system

,A model is a high-level representation of the operation of a real-world process or system.
Models can be discrete (changes at discrete points in time), continuous (changes
continuously), stochastic (probabilistic), or deterministic (no randomness involved) .



Q2. What is simulation defined as?

A) The exact replication of a system
B) The imitation of a real-world process or system over time
C) The mathematical analysis of a system
D) The physical modeling of a system

Correct Answer: B. The imitation of a real-world process or system over time

Simulation is the imitation of a real-world process or system over time. It involves creating a
model and running it to observe system behavior .



Q3. Which of the following is an example of a discrete model?

A) Weather forecasting over time
B) Customer arrivals at a store
C) The velocity of a falling object
D) Water flow in a river

Correct Answer: B. Customer arrivals at a store

A discrete model involves changes happening at discrete points in time, such as customers
arriving and leaving at a store. Continuous models involve changes that happen
continuously, like weather or water flow .

,Q4. Which type of model involves probability and randomness?

A) Deterministic model
B) Stochastic model
C) Static model
D) Continuous model

Correct Answer: B. Stochastic model

Stochastic models are probabilistic models that involve randomness. Monte Carlo
simulation is a classic example. Deterministic models allow you to calculate a future event
exactly without randomness .



Q5. What was the first example of simulation historically?

A) Gossett's t-distribution
B) Buffon's needle problem (1777)
C) The Manhattan Project simulations
D) Markowitz's portfolio optimization

Correct Answer: B. Buffon's needle problem (1777)

The first example of simulation occurred in 1777 with Buffon's needle problem, which
involved dropping needles between parallel lines to estimate pi .



Q6. Who won the 1990 Nobel Prize in Economics for portfolio optimization?

A) William Gossett
B) Harry Markowitz (with Merton Miller & William Sharpe)

, C) Ulam, Metropolis, and von Neumann
D) Comte de Buffon

Correct Answer: B. Harry Markowitz (with Merton Miller & William Sharpe)

Harry Markowitz won the 1990 Nobel Prize in Economics for his work in portfolio
optimization. He also invented the SimScript simulation language. He shared the prize with
Merton Miller and William Sharpe .



Q7. Which situation(s) might be good candidates to use simulation?

A) A savings account with 2% continuously compounded interest
B) Investing half in bonds and half in a stock market equity index
C) A new strategy for baseball batting orders
D) An assembly station with random interarrival times and random service times
E) All of the above except A

Correct Answer: E. All of the above except A

The savings account scenario is deterministic and can be solved analytically. The other
scenarios involve randomness and complex interactions that make simulation appropriate.
Simulation is useful when there is randomness and complexity .



Q8. What is the difference between deterministic and stochastic models?

A) Deterministic models include randomness; stochastic models do not
B) Deterministic models allow exact calculation without randomness; stochastic models
involve probability

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