Question 1

Each different set of values obtained for the uncertain quantities in a simulation model can considered to be:

Accepted Answer

A) the mean of the probability distribution. 
B) a scenario. 
C) a best guess. 
D) all of these options. 
A) the mean of the probability distribution. 
B) a scenario. 
C) a best guess. 
D) all of these options. B

Question 2

Use @Risk simulation add-in to analyze the sweatshirt sales.Do this for normal distributions,where we assume that the regular demand is normally distributed with mean 10,000 and standard deviation 1500,and that the demand at the reduced price is normally distributed with mean 5,000 and standard deviation 1500.

Accepted Answer

Single simulation replication

Question 3

We sometimes use discrete distributions in place of continuous distributions:

Accepted Answer

A) because they are more accurate. 
B) because they are more simple. 
C) when we don't know the mean and variance of the distribution. 
D) when we need to generate a histogram 
A) because they are more accurate. 
B) because they are more simple. 
C) when we don't know the mean and variance of the distribution. 
D) when we need to generate a histogram B

Question 4

If we want to model the time it takes to serve a customer at a bank,we will probably choose

Accepted Answer

A) symmetric distribution 
B) positively skewed distribution 
C) negatively skewed distribution 
D) All of these options 
A) symmetric distribution 
B) positively skewed distribution 
C) negatively skewed distribution 
D) All of these options

Question 5

It is common in computer simulations to estimate the mean of some distribution by the average of the simulated observations.The usual practice is then to accompany this estimate with a confidence interval,which indicates the accuracy of the estimate.

Accepted Answer

A) True 
 B)False

Question 6

Data tables in spreadsheet simulations are useful for taking a "prototype" simulation and replicating its key results a desired number of times.

Accepted Answer

A) True 
 B)False

Question 7

(A)Use a simulation model to help the institute decide how many violins they must reserve with the instrument company.Consider five different possible reservation quantities: 400,500,600,700,800.Which of these quantities yields the highest total revenue,net of instrument costs?
(B)Which simulation yields the largest median total revenue?
(C)Which simulation has the most risk as measured by spread or dispersion in the data? Please state clearly what statistic you used to answer this question.
(D)Are there any simulations in which there is at least a 1 in 20 (i.e.,5%)chance of getting a negative total revenue? Briefly explain in one sentence.
(E)For each simulation what is the probability of exceeding $175,000 in total revenue (approximate these numbers as closely as possible from the data given in the above table).Please put your answer in the following table:
   (F)Considering your answers for (A)through (E),please state how many instruments you think should be reserved in advance and explain why.
(G)Suppose the institute is able to negotiate with the instrument company to reduce the cost for a violin from $500 to $350.Re-run the simulation model using the same reservation quantities (but with $350 for the unused instrument cost).Has the reservation quantity that yields the highest average revenue changed? If so,please explain why this has occurred.

Accepted Answer

(A)Simulation 3 (Q=600 instruments)yield

Question 8

In order to generate random numbers in Excel from a discrete distribution with a finite number of possible values and corresponding probabilities,we can use

Accepted Answer

A) only the RAND function 
B) only the VLOOKUP function 
C) only the VLOOKDOWN function 
D) the RAND function along with a VLOOKUP function 
A) only the RAND function 
B) only the VLOOKUP function 
C) only the VLOOKDOWN function 
D) the RAND function along with a VLOOKUP function

Question 9

Which of the following statements is true regarding a simulation model?

Accepted Answer

A) It explicitly models decision-making under uncertainty 
B) It explicitly incorporates uncertainty in one or more input variables 
C) It provides probability distributions for all outputs,rather than expected values 
D) All of these options 
A) It explicitly models decision-making under uncertainty 
B) It explicitly incorporates uncertainty in one or more input variables 
C) It provides probability distributions for all outputs,rather than expected values 
D) All of these options

Question 10

Which of the following statements are true?

Accepted Answer

A) The @RISK contains a number of functions such as RISKNORMAL and RISKDISCRETE that make it easy to generate observations from the most important probability distributions. 
B) You can specify any cell or range of cells in your simulation model as output cells.When you run the simulation,@RISK automatically keeps summary measures (averages,standard deviation,percentiles,and others)from the values generated in these output cells across the replications. 
C) @RISK has a special function,RISKSIMTABLE,which allows you to run the same simulation several times,using a different value of some key input variable each time. 
D) All of the above 
A) The @RISK contains a number of functions such as RISKNORMAL and RISKDISCRETE that make it easy to generate observations from the most important probability distributions. 
B) You can specify any cell or range of cells in your simulation model as output cells.When you run the simulation,@RISK automatically keeps summary measures (averages,standard deviation,percentiles,and others)from the values generated in these output cells across the replications. 
C) @RISK has a special function,RISKSIMTABLE,which allows you to run the same simulation several times,using a different value of some key input variable each time. 
D) All of the above

Question 11

Assume that x is a random number between 0 and 1,and that the number of units expected to be sold is uniformly distributed between 300 and 500.Then,sales are given by the expression

Accepted Answer

A) 300 + x 
B) 500 - x 
C) 300 + 200 x 
D) 500 - 200 x 
E) 300 + 500 x 
A) 300 + x 
B) 500 - x 
C) 300 + 200 x 
D) 500 - 200 x 
E) 300 + 500 x

Question 12

Use simulation to analyze the supplier's problem.Determine how many sweatshirts he should produce to maximize the expected profit.

Accepted Answer

Data table for average profit as functio

Question 13

Company experts believe the development time will be from 5 to 9 months,but they have absolutely no idea which of these will result.

Accepted Answer

The "no idea" sugges

Question 14

The uniform distribution is bounded by a minimum and a maximum,and all values between these two extremes are equally likely.

Accepted Answer

A) True 
 B)False

Question 15

Company experts believe the development time will from 5 to 9 months.They believe the probabilities of the extremes (5 and 9 months)are both 10%,and the probabilities will vary linearly from those endpoints to a most likely value at 7 months.

Accepted Answer

This is a general discrete distribution.

Question 16

Spreadsheet simulation modeling is quite similar to the other modeling applications in that it begins with input variables and then relates these with appropriate Excel formulas to produce output variables of interest.

Accepted Answer

A) True 
 B)False

Question 17

One of the primary advantages of simulation models that they enable managers to answer what-if questions about changes in systems without actually changing the systems themselves.

Accepted Answer

A) True 
 B)False

Question 18

It is simple to generate a uniformly distributed random number with a minimum and maximum other than 0 and 1.For example,the formula =150+100   RAND()generates a number uniformly distributed between

Accepted Answer

A) 100 and 150 
B) 150 and 250 
C) 50 and 100 
D) 50 and 250 
A) 100 and 150 
B) 150 and 250 
C) 50 and 100 
D) 50 and 250

Question 19

When we maximize or minimize the value of a decision variable by running several simulations simultaneously,we have found an optimal solution to the problem and attitude toward risk becomes irrelevant.

Accepted Answer

A) True 
 B)False

Question 20

The normal distribution is often used in simulation models because it is the most common distribution in statistics and it does not allow negative values.

Accepted Answer

A) True 
 B)False

Each different set of values obtained for the uncertain quantities in a simulation model can considered to be:

We sometimes use discrete distributions in place of continuous distributions:

If we want to model the time it takes to serve a customer at a bank,we will probably choose

It is common in computer simulations to estimate the mean of some distribution by the average of the simulated observations.The usual practice is then to accompany this estimate with a confidence interval,which indicates the accuracy of the estimate.

Data tables in spreadsheet simulations are useful for taking a "prototype" simulation and replicating its key results a desired number of times.

In order to generate random numbers in Excel from a discrete distribution with a finite number of possible values and corresponding probabilities,we can use

Which of the following statements is true regarding a simulation model?

Which of the following statements are true?

Assume that x is a random number between 0 and 1,and that the number of units expected to be sold is uniformly distributed between 300 and 500.Then,sales are given by the expression

Use simulation to analyze the supplier's problem.Determine how many sweatshirts he should produce to maximize the expected profit.

Company experts believe the development time will be from 5 to 9 months,but they have absolutely no idea which of these will result.

The uniform distribution is bounded by a minimum and a maximum,and all values between these two extremes are equally likely.

Company experts believe the development time will from 5 to 9 months.They believe the probabilities of the extremes (5 and 9 months)are both 10%,and the probabilities will vary linearly from those endpoints to a most likely value at 7 months.

Spreadsheet simulation modeling is quite similar to the other modeling applications in that it begins with input variables and then relates these with appropriate Excel formulas to produce output variables of interest.

One of the primary advantages of simulation models that they enable managers to answer what-if questions about changes in systems without actually changing the systems themselves.

It is simple to generate a uniformly distributed random number with a minimum and maximum other than 0 and 1.For example,the formula =150+100 RAND()generates a number uniformly distributed between

When we maximize or minimize the value of a decision variable by running several simulations simultaneously,we have found an optimal solution to the problem and attitude toward risk becomes irrelevant.

The normal distribution is often used in simulation models because it is the most common distribution in statistics and it does not allow negative values.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Modeling: Applications

Simulation Models

Filters

Exam 15: Introduction to Simulation Modeling

Each different set of values obtained for the uncertain quantities in a simulation model can considered to be:

We sometimes use discrete distributions in place of continuous distributions:

If we want to model the time it takes to serve a customer at a bank,we will probably choose

It is common in computer simulations to estimate the mean of some distribution by the average of the simulated observations.The usual practice is then to accompany this estimate with a confidence interval,which indicates the accuracy of the estimate.

Data tables in spreadsheet simulations are useful for taking a "prototype" simulation and replicating its key results a desired number of times.

In order to generate random numbers in Excel from a discrete distribution with a finite number of possible values and corresponding probabilities,we can use

Which of the following statements is true regarding a simulation model?

Which of the following statements are true?

Assume that x is a random number between 0 and 1,and that the number of units expected to be sold is uniformly distributed between 300 and 500.Then,sales are given by the expression

Use simulation to analyze the supplier's problem.Determine how many sweatshirts he should produce to maximize the expected profit.

Company experts believe the development time will be from 5 to 9 months,but they have absolutely no idea which of these will result.

The uniform distribution is bounded by a minimum and a maximum,and all values between these two extremes are equally likely.

Company experts believe the development time will from 5 to 9 months.They believe the probabilities of the extremes (5 and 9 months)are both 10%,and the probabilities will vary linearly from those endpoints to a most likely value at 7 months.

Spreadsheet simulation modeling is quite similar to the other modeling applications in that it begins with input variables and then relates these with appropriate Excel formulas to produce output variables of interest.

One of the primary advantages of simulation models that they enable managers to answer what-if questions about changes in systems without actually changing the systems themselves.

It is simple to generate a uniformly distributed random number with a minimum and maximum other than 0 and 1.For example,the formula =150+100 RAND()generates a number uniformly distributed between

When we maximize or minimize the value of a decision variable by running several simulations simultaneously,we have found an optimal solution to the problem and attitude toward risk becomes irrelevant.

The normal distribution is often used in simulation models because it is the most common distribution in statistics and it does not allow negative values.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Modeling: Applications

Simulation Models

Filters