Question 1

In bidding models,the simulation input variable is the number of competitors who will bid.

Accepted Answer

A) True 
 B)False

Question 2

Which of the following functions is not appropriate in cases where we run a single simulation?

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 3

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 4

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 5

Does the answer to Question 72 match your intuition? Explain why or why not.
In this example we are estimating the net present value of introducing a new drug to market.We have the following information about the market:
· The market size is 1,000,000 and is projected to grow at an average 5%,with a standard deviation of 1%,over the next ten years.
· The market share captured at entry is projected to be between 20% and 70%,with most likely value 40%.
· Three competitors may enter the market in the future,with each one having a 40% probability of entry per year.
· For each new competitor per year,the market share goes down by 20%.
· The marginal profit per unit is $1.80.
· We want to evaluate the project over ten years,using a discount rate of 10%.

Accepted Answer

However,we must simulate to find the cor

Question 6

We can use the RISKSIMTABLE function to summarize the results of a single simulation of product lifetime.

Accepted Answer

A) True 
 B)False

Question 7

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

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is not among the financial applications where simulation can be applied?

Accepted Answer

A)  Future stock prices 
B)  Customer preferences for different attributes of products 
C)  Future interest rates 
D)  Future cash flows 
E)  None of these options 
A)  Future stock prices 
B)  Customer preferences for different attributes of products 
C)  Future interest rates 
D)  Future cash flows 
E)  None of these options

Question 9

Develop an @Risk model to estimate the NPV given an assumed capacity.What are the variable inputs and outputs?

Accepted Answer

The random variable inputs are the marke

Question 10

In marketing models of customer loyalty,we are typically interested in modeling the rate of customer retention,called churn.

Accepted Answer

A) True 
 B)False

Question 11

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 12

In investment models,a useful approach for generating future returns and inflation factors from historical data is:

Accepted Answer

A)  the NPV approach 
B)  the scenario approach 
C)  the averaging approach 
D)  the trend analysis approach 
E)  None of these options 
A)  the NPV approach 
B)  the scenario approach 
C)  the averaging approach 
D)  the trend analysis approach 
E)  None of these options

Question 13

In a manufacturing setting,a discrete distribution is natural for modeling the number of days to produce a batch,and a continuous distribution is appropriate for modeling the yield from a batch.

Accepted Answer

A) True 
 B)False

Question 14

In cash flow models,we are typically interested in investigating:

Accepted Answer

A)  the value at risk (VAR) 
B)  the net present value (NPV) 
C)  the amount of loans required to maintain a minimum cash balance 
D)  the interest on loans taken out by a firm 
E)  None of these options 
A)  the value at risk (VAR) 
B)  the net present value (NPV) 
C)  the amount of loans required to maintain a minimum cash balance 
D)  the interest on loans taken out by a firm 
E)  None of these options

Question 15

Cash balance models are an example of which of the following types of simulation application?

Accepted Answer

A)  Operations models 
B)  Financial models 
C)  Marketing models 
D)  Games of chance 
E)  None of these options 
A)  Operations models 
B)  Financial models 
C)  Marketing models 
D)  Games of chance 
E)  None of these options

Question 16

In a manufacturing model,we might simulate the number of days to produce a batch and the yield from each batch.The number of days would typically be a ___________ distribution and the yield would be a ___________ distribution.

Accepted Answer

A)  Continuous,discrete 
B)  Continuous,continuous 
C)  Discrete,continuous 
D)  Discrete,discrete
Amanda is a recent college graduate,and has just started her first job.She would like to know if she saves $5,000 per year out of her salary over the next 30 years what the distribution of the value of her retirement fund after 30 years.She has decided that she will invest all her money in the stock market that she estimates has a return that is normally distributed with mean 12% per year and standard deviation 25%. 
A)  Continuous,discrete 
B)  Continuous,continuous 
C)  Discrete,continuous 
D)  Discrete,discrete
Amanda is a recent college graduate,and has just started her first job.She would like to know if she saves $5,000 per year out of her salary over the next 30 years what the distribution of the value of her retirement fund after 30 years.She has decided that she will invest all her money in the stock market that she estimates has a return that is normally distributed with mean 12% per year and standard deviation 25%.

Question 17

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 18

Customer loyalty models are an example of which of the following types of simulation application?

Accepted Answer

A)  Operations models 
B)  Financial models 
C)  Marketing models 
D)  Games of chance 
E)  None of these options 
A)  Operations models 
B)  Financial models 
C)  Marketing models 
D)  Games of chance 
E)  None of these options

Question 19

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 20

A common distribution for modeling product lifetimes is the binomial distribution

Accepted Answer

A) True 
 B)False

In bidding models,the simulation input variable is the number of competitors who will bid.

Which of the following functions is not appropriate in cases where we run a single simulation?

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

We can use the RISKSIMTABLE function to summarize the results of a single simulation of product lifetime.

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

Which of the following is not among the financial applications where simulation can be applied?

Develop an @Risk model to estimate the NPV given an assumed capacity.What are the variable inputs and outputs?

In marketing models of customer loyalty,we are typically interested in modeling the rate of customer retention,called churn.

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

In investment models,a useful approach for generating future returns and inflation factors from historical data is:

In a manufacturing setting,a discrete distribution is natural for modeling the number of days to produce a batch,and a continuous distribution is appropriate for modeling the yield from a batch.

In cash flow models,we are typically interested in investigating:

Cash balance models are an example of which of the following types of simulation application?

In a manufacturing model,we might simulate the number of days to produce a batch and the yield from each batch.The number of days would typically be a _ distribution and the yield would be a _ distribution.

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.

Customer loyalty models are an example of which of the following types of simulation application?

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

A common distribution for modeling product lifetimes is the binomial distribution

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 Models

Introduction to Simulation Modeling

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 16: Simulation Models

In bidding models,the simulation input variable is the number of competitors who will bid.

Which of the following functions is not appropriate in cases where we run a single simulation?

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

We can use the RISKSIMTABLE function to summarize the results of a single simulation of product lifetime.

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

Which of the following is not among the financial applications where simulation can be applied?

Develop an @Risk model to estimate the NPV given an assumed capacity.What are the variable inputs and outputs?

In marketing models of customer loyalty,we are typically interested in modeling the rate of customer retention,called churn.

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

In investment models,a useful approach for generating future returns and inflation factors from historical data is:

In a manufacturing setting,a discrete distribution is natural for modeling the number of days to produce a batch,and a continuous distribution is appropriate for modeling the yield from a batch.

In cash flow models,we are typically interested in investigating:

Cash balance models are an example of which of the following types of simulation application?

In a manufacturing model,we might simulate the number of days to produce a batch and the yield from each batch.The number of days would typically be a ___________ distribution and the yield would be a ___________ distribution.

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.

Customer loyalty models are an example of which of the following types of simulation application?

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

A common distribution for modeling product lifetimes is the binomial distribution

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 Models

Introduction to Simulation Modeling

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

In a manufacturing model,we might simulate the number of days to produce a batch and the yield from each batch.The number of days would typically be a _ distribution and the yield would be a _ distribution.