Question 1

In warranty cost models,the key input random variable is product lifetime.

Accepted Answer

A) True 
 B)False

Question 2

In marketing and sales models,the primary issue is the uncertain amount of sales that can be obtained,given an assumed timing.

Accepted Answer

A) True 
 B)False

Question 3

Financial analysts often investigate the value at risk (VAR)with simulation models.VAR is an indicator of:

Accepted Answer

A) how much to bid for a project 
B) the expected amount of loss for a project 
C) what is nearly the worst possible outcome for a project 
D) the required amount of investment required for a project 
E) None of these options 
A) how much to bid for a project 
B) the expected amount of loss for a project 
C) what is nearly the worst possible outcome for a project 
D) the required amount of investment required for a project 
E) None of these options

Question 4

Simulate the price of the stock in five years by calculating five annual increments (steps)with this model,starting from the current price of $30/share.For each price simulated five years from now,model the exercise decision and calculate the resulting profit,which should then be discounted for five years at the current discount rate (5%)to obtain the present value of the options.What is the expected value of the stock options?

Accepted Answer

The mean discounted

Question 5

We can use Excel's RAND function inside an IF function to simulate whether some event occurs or does not occur.

Accepted Answer

A) True 
 B)False

Question 6

Until uncertainty about the growth rate is resolved,the volatility of the stock price could well be much higher than 18% - perhaps as high at 25%.What would the value be in that case?

Accepted Answer

The increase in unce

Question 7

Which of the following functions is not an @RISK statistical function?

Accepted Answer

A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKSIMTABLE 
E) None of these options 
A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKSIMTABLE 
E) None of these options

Question 8

The Net Present Value (NPV)is the sum of the discounted cash flows.What is the NPV of the project,including the required investment?

Accepted Answer

Including the requir

Question 9

Are there any simulations which indicated there was a chance of getting negative NPV? Briefly explain in one sentence.

Accepted Answer

Yes.Both simulations 4 and 5 (Q=35,000 u

Question 10

Simulation applications involving games of chance are primarily for learning the background of simulation (e.g.,modeling gambling casinos of Monte Carlo),since they are not business applications per se.

Accepted Answer

A) True 
 B)False

Question 11

The @RISK function RISKDUNIFORM in the form = RISKDUNIFORM ({List})generates a random member of a given list,so that each member of the list has the same chance of being chosen.

Accepted Answer

A) True 
 B)False

Question 12

What if the GM satisfaction rate is raised further to 90%.What would the customer NPV be in that case?

Accepted Answer

Raising customer sat

Question 13

Given your answers to Questions 51 through 55,would you invest in this project?

Accepted Answer

Although this project has a po

Question 14

What is the probability of winning for each bidder in the above scenario?

Accepted Answer

We could simulate this as an o

Question 15

Using @RISK summary functions such as RISKMEAN,RISKPERCENTILE,and others allows us to capture simulation results in the same worksheet as the simulation model.

Accepted Answer

A) True 
 B)False

Question 16

The primary objective in simulation models of bidding for contracts is to determine the optimal bid.

Accepted Answer

A) True 
 B)False

Question 17

A tornado chart lets us see which random input has the most effect on a specified output in a financial model.

Accepted Answer

A) True 
 B)False

Question 18

What is the probability that Amanda will have less than $500,000 in her retirement account after 30 years?

Accepted Answer

Using the output graph with sl

Question 19

Suppose we compare the difference between the NPV of a financial model in which the means are entered for all input random variables and the NPV of a financial model in which the most likely values are entered for all input random variables.If we see a large difference between the NPV's,this illustrates:

Accepted Answer

A) the value at risk (VAR) 
B) the effect of randomness 
C) the flaw of averages 
D) the bias of the analyst 
E) None of these options 
A) the value at risk (VAR) 
B) the effect of randomness 
C) the flaw of averages 
D) the bias of the analyst 
E) None of these options

Question 20

Which of the following is among the questions that financial analysts try to answer with simulation models?

Accepted Answer

A) Mean and variance of a project NPV 
B) Probability that a project with have a negative NPV 
C) Probability that a company will have to borrow a certain amount during the next year 
D) Mean and variance of a company's profit during the next fiscal year 
E) All of these options 
A) Mean and variance of a project NPV 
B) Probability that a project with have a negative NPV 
C) Probability that a company will have to borrow a certain amount during the next year 
D) Mean and variance of a company's profit during the next fiscal year 
E) All of these options

In warranty cost models,the key input random variable is product lifetime.

In marketing and sales models,the primary issue is the uncertain amount of sales that can be obtained,given an assumed timing.

Financial analysts often investigate the value at risk (VAR)with simulation models.VAR is an indicator of:

We can use Excel's RAND function inside an IF function to simulate whether some event occurs or does not occur.

Until uncertainty about the growth rate is resolved,the volatility of the stock price could well be much higher than 18% - perhaps as high at 25%.What would the value be in that case?

Which of the following functions is not an @RISK statistical function?

The Net Present Value (NPV)is the sum of the discounted cash flows.What is the NPV of the project,including the required investment?

Are there any simulations which indicated there was a chance of getting negative NPV? Briefly explain in one sentence.

Simulation applications involving games of chance are primarily for learning the background of simulation (e.g.,modeling gambling casinos of Monte Carlo),since they are not business applications per se.

The @RISK function RISKDUNIFORM in the form = RISKDUNIFORM ({List})generates a random member of a given list,so that each member of the list has the same chance of being chosen.

What if the GM satisfaction rate is raised further to 90%.What would the customer NPV be in that case?

Given your answers to Questions 51 through 55,would you invest in this project?

What is the probability of winning for each bidder in the above scenario?

Using @RISK summary functions such as RISKMEAN,RISKPERCENTILE,and others allows us to capture simulation results in the same worksheet as the simulation model.

The primary objective in simulation models of bidding for contracts is to determine the optimal bid.

A tornado chart lets us see which random input has the most effect on a specified output in a financial model.

What is the probability that Amanda will have less than $500,000 in her retirement account after 30 years?

Which of the following is among the questions that financial analysts try to answer with simulation models?

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

Introduction to Simulation Modeling

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Exam 16: Simulation Models

In warranty cost models,the key input random variable is product lifetime.

In marketing and sales models,the primary issue is the uncertain amount of sales that can be obtained,given an assumed timing.

Financial analysts often investigate the value at risk (VAR)with simulation models.VAR is an indicator of:

We can use Excel's RAND function inside an IF function to simulate whether some event occurs or does not occur.

Until uncertainty about the growth rate is resolved,the volatility of the stock price could well be much higher than 18% - perhaps as high at 25%.What would the value be in that case?

Which of the following functions is not an @RISK statistical function?

The Net Present Value (NPV)is the sum of the discounted cash flows.What is the NPV of the project,including the required investment?

Are there any simulations which indicated there was a chance of getting negative NPV? Briefly explain in one sentence.

Simulation applications involving games of chance are primarily for learning the background of simulation (e.g.,modeling gambling casinos of Monte Carlo),since they are not business applications per se.

The @RISK function RISKDUNIFORM in the form = RISKDUNIFORM ({List})generates a random member of a given list,so that each member of the list has the same chance of being chosen.

What if the GM satisfaction rate is raised further to 90%.What would the customer NPV be in that case?

Given your answers to Questions 51 through 55,would you invest in this project?

What is the probability of winning for each bidder in the above scenario?

Using @RISK summary functions such as RISKMEAN,RISKPERCENTILE,and others allows us to capture simulation results in the same worksheet as the simulation model.

The primary objective in simulation models of bidding for contracts is to determine the optimal bid.

A tornado chart lets us see which random input has the most effect on a specified output in a financial model.

What is the probability that Amanda will have less than $500,000 in her retirement account after 30 years?

Which of the following is among the questions that financial analysts try to answer with simulation models?

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

Introduction to Simulation Modeling

Filters