Question 1

Which of the following parameters is required to convert a computer-generated random variable into a uniform random variable?

Accepted Answer

A) Range of the distribution 
B) Mean of the distribution 
C) Variance of the distribution 
D) Moments of the distribution 
A) Range of the distribution 
B) Mean of the distribution 
C) Variance of the distribution 
D) Moments of the distribution

Question 2

In a base-case scenario, the output is determined by assuming

Accepted Answer

A) worst values that can be expected for the random variables of a model. 
B) the mean trial values for the random variables of a model. 
C) best values that can be expected for the random variables of a model. 
D) the most likely values for the random variables of a model. 
A) worst values that can be expected for the random variables of a model. 
B) the mean trial values for the random variables of a model. 
C) best values that can be expected for the random variables of a model. 
D) the most likely values for the random variables of a model.

Question 3

Which of the following cannot be described by a discrete probability distribution?

Accepted Answer

A) Sales of two medical devices in which Device A generates $35 per unit sold and will likely constitute 30% of the sales and Device B generates $50 per unit sold and will likely constitute 70% of the sales. 
B) The labor cost for manufacturing goods, where one-third of the units cost $10 in labor, one-third cost $15 in labor, and one-third cost $50 in labor. 
C) The cost of parts for manufacturing an item, where the parts can take on any value between $80 and $100. 
D) The number of units produced in a given day, where 20% of the time 99 units are produced and 80% of the time 100 units are produced. 
A) Sales of two medical devices in which Device A generates $35 per unit sold and will likely constitute 30% of the sales and Device B generates $50 per unit sold and will likely constitute 70% of the sales. 
B) The labor cost for manufacturing goods, where one-third of the units cost $10 in labor, one-third cost $15 in labor, and one-third cost $50 in labor. 
C) The cost of parts for manufacturing an item, where the parts can take on any value between $80 and $100. 
D) The number of units produced in a given day, where 20% of the time 99 units are produced and 80% of the time 100 units are produced.

Question 4

The __________ function in Excel is used to compute the statistics required to create a histogram.

Accepted Answer

A) NORM.INV 
B) RAND 
C) FREQUENCY 
D) STDEV.S 
A) NORM.INV 
B) RAND 
C) FREQUENCY 
D) STDEV.S

Question 5

The choice of the probability distribution for a random variable can be guided by

Accepted Answer

A) an objective function. 
B) likelihood factors. 
C) forecasting. 
D) historical data. 
A) an objective function. 
B) likelihood factors. 
C) forecasting. 
D) historical data.

Question 6

A simulation model extends spreadsheet modeling by

Accepted Answer

A) extending the range of parameters for which solutions are computed. 
B) using real-time values for parameters from the application to formulate solutions. 
C) replacing the use of single values for parameters with a range of possible values. 
D) using historical data to make predictions about future values and expected trends. 
A) extending the range of parameters for which solutions are computed. 
B) using real-time values for parameters from the application to formulate solutions. 
C) replacing the use of single values for parameters with a range of possible values. 
D) using historical data to make predictions about future values and expected trends.

Question 7

A description of the range and relative likelihood of possible values of an uncertain variable is known as a

Accepted Answer

A) risk analysis. 
B) probability distribution. 
C) base-case scenario. 
D) simulation optimization. 
A) risk analysis. 
B) probability distribution. 
C) base-case scenario. 
D) simulation optimization.

Question 8

A ___________ uses repeated random sampling to represent uncertainty in a model representing a real system and that computes the values of model outputs.

Accepted Answer

A) Monte Carlo simulation 
B) what-if analysis 
C) deterministic model 
D) discrete event simulation 
A) Monte Carlo simulation 
B) what-if analysis 
C) deterministic model 
D) discrete event simulation

Question 9

A disadvantage of the simple what-if analyses is that

Accepted Answer

A) there are errors induced as a result of rounding. 
B) the optimal solutions are not guaranteed. 
C) there is no indication of the likelihood of various output values. 
D) it cannot compute alternate optimal solutions. 
A) there are errors induced as a result of rounding. 
B) the optimal solutions are not guaranteed. 
C) there is no indication of the likelihood of various output values. 
D) it cannot compute alternate optimal solutions.

Question 10

The range of computer-generated random numbers is

Accepted Answer

A) [-8, 8]. 
B) [-8, 0). 
C) [1, 8]. 
D) [0, 1). 
A) [-8, 8]. 
B) [-8, 0). 
C) [1, 8]. 
D) [0, 1).

Question 11

All the values of computer-generated random numbers are

Accepted Answer

A) Poisson distributed. 
B) lognormally distributed. 
C) uniformly distributed. 
D) normally distributed. 
A) Poisson distributed. 
B) lognormally distributed. 
C) uniformly distributed. 
D) normally distributed.

Question 12

The __________ function is used to generate a pseudorandom number in Excel.

Accepted Answer

A) FREQUENCY() 
B) RAND() 
C) NORM.INV() 
D) ROUND() 
A) FREQUENCY() 
B) RAND() 
C) NORM.INV() 
D) ROUND()

Question 13

Which of the following cannot be modeled by a continuous distribution?

Accepted Answer

A) Length of time it takes to manufacture a product 
B) Height of the finished manufactured product 
C) Weight of a finished manufactured product 
D) Number of products produced in an hour 
A) Length of time it takes to manufacture a product 
B) Height of the finished manufactured product 
C) Weight of a finished manufactured product 
D) Number of products produced in an hour

Question 14

A(n) __________ is an input to a simulation model whose value is uncertain and described by a probability distribution.

Accepted Answer

A) identifier 
B) constraint 
C) random variable 
D) decision variable 
A) identifier 
B) constraint 
C) random variable 
D) decision variable

Question 15

The values for random variables in a Monte Carlo simulation are

Accepted Answer

A) selected manually. 
B) generated randomly from probability distributions. 
C) taken from forecasting analysis. 
D) derived secondarily using formulas. 
A) selected manually. 
B) generated randomly from probability distributions. 
C) taken from forecasting analysis. 
D) derived secondarily using formulas.

Question 16

Which of the following numbers cannot result from the Excel function =NORM.INV(RAND( ), 100, 10)?

Accepted Answer

A) 99 
B) 115 
C) 121 
D) All of these numbers can result from this Excel function. 
A) 99 
B) 115 
C) 121 
D) All of these numbers can result from this Excel function.

Question 17

The process of determining that a computer program implements a simulation model as it is intended is known as

Accepted Answer

A) validation. 
B) verification. 
C) correlation. 
D) optimization. 
A) validation. 
B) verification. 
C) correlation. 
D) optimization.

Question 18

The outcome of a simulation experiment is a(n)

Accepted Answer

A) objective function. 
B) probability distribution for one or more output measures. 
C) single number. 
D) what-if scenario. 
A) objective function. 
B) probability distribution for one or more output measures. 
C) single number. 
D) what-if scenario.

Question 19

Which of the following functions computes a value such that 2.5% of the area under the standard normal distribution lies in the upper tail defined by this value?

Accepted Answer

A) =NORM.S.INV(0.975) 
B) =NORM.S.INV(0.025) 
C) =NORM.S.INV(0.05) 
D) =NORM.S.INV(0.95) 
A) =NORM.S.INV(0.975) 
B) =NORM.S.INV(0.025) 
C) =NORM.S.INV(0.05) 
D) =NORM.S.INV(0.95)

Question 20

The process of evaluating a decision in the face of uncertainty by quantifying the likelihood and magnitude of an undesirable outcome is known as

Accepted Answer

A) risk analysis. 
B) regression analysis. 
C) data mining. 
D) decision tree analysis. 
A) risk analysis. 
B) regression analysis. 
C) data mining. 
D) decision tree analysis.

Which of the following parameters is required to convert a computer-generated random variable into a uniform random variable?

In a base-case scenario, the output is determined by assuming

Which of the following cannot be described by a discrete probability distribution?

The __________ function in Excel is used to compute the statistics required to create a histogram.

The choice of the probability distribution for a random variable can be guided by

A simulation model extends spreadsheet modeling by

A description of the range and relative likelihood of possible values of an uncertain variable is known as a

A ___________ uses repeated random sampling to represent uncertainty in a model representing a real system and that computes the values of model outputs.

A disadvantage of the simple what-if analyses is that

The range of computer-generated random numbers is

All the values of computer-generated random numbers are

The __________ function is used to generate a pseudorandom number in Excel.

Which of the following cannot be modeled by a continuous distribution?

A(n) __________ is an input to a simulation model whose value is uncertain and described by a probability distribution.

The values for random variables in a Monte Carlo simulation are

Which of the following numbers cannot result from the Excel function =NORM.INV(RAND( ), 100, 10)?

The process of determining that a computer program implements a simulation model as it is intended is known as

The outcome of a simulation experiment is a(n)

Which of the following functions computes a value such that 2.5% of the area under the standard normal distribution lies in the upper tail defined by this value?

The process of evaluating a decision in the face of uncertainty by quantifying the likelihood and magnitude of an undesirable outcome is known as

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters

Exam 11: Monte Carlo Simulation

Which of the following parameters is required to convert a computer-generated random variable into a uniform random variable?

In a base-case scenario, the output is determined by assuming

Which of the following cannot be described by a discrete probability distribution?

The __________ function in Excel is used to compute the statistics required to create a histogram.

The choice of the probability distribution for a random variable can be guided by

A simulation model extends spreadsheet modeling by

A description of the range and relative likelihood of possible values of an uncertain variable is known as a

A ___________ uses repeated random sampling to represent uncertainty in a model representing a real system and that computes the values of model outputs.

A disadvantage of the simple what-if analyses is that

The range of computer-generated random numbers is

All the values of computer-generated random numbers are

The __________ function is used to generate a pseudorandom number in Excel.

Which of the following cannot be modeled by a continuous distribution?

A(n) __________ is an input to a simulation model whose value is uncertain and described by a probability distribution.

The values for random variables in a Monte Carlo simulation are

Which of the following numbers cannot result from the Excel function =NORM.INV(RAND( ), 100, 10)?

The process of determining that a computer program implements a simulation model as it is intended is known as

The outcome of a simulation experiment is a(n)

Which of the following functions computes a value such that 2.5% of the area under the standard normal distribution lies in the upper tail defined by this value?

The process of evaluating a decision in the face of uncertainty by quantifying the likelihood and magnitude of an undesirable outcome is known as

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters