Question 1

If the warranty period were reduced to 2 years,how much per year in replacement costs would be saved?

Accepted Answer

@#IMG-DLM& Having a 3-year warranty instead of a 2

Question 2

RISKMAX and RISKMIN are can be used to find the probability of meeting a given due date in a manufacturing model.

Accepted Answer

A) True 
 B)False

Question 3

What is an example of a financial application in which simulation cannot be applied?

Accepted Answer

A) Future stock prices 
B) Customer preferences for different attributes of products 
C) Future interest rates 
D) Future cash flows 
A) Future stock prices 
B) Customer preferences for different attributes of products 
C) Future interest rates 
D) Future cash flows

Question 4

A key input variable in many marketing models of customer loyalty is the

Accepted Answer

A) mean profit per customer. 
B) number of customers. 
C) churn rate. 
D) time horizon. 
A) mean profit per customer. 
B) number of customers. 
C) churn rate. 
D) time horizon.

Question 5

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

Accepted Answer

A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKSIMTABLE 
A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKSIMTABLE

Question 6

Bidding for contracts is an example of which category of simulation model application?

Accepted Answer

A) Operations models 
B) Financial models 
C) Marketing models 
D) Games of chance 
A) Operations models 
B) Financial models 
C) Marketing models 
D) Games of chance

Question 7

What is the probability that your portfolio's annual return will exceed 20%?

Accepted Answer

@#IMG-DLM& Since there is a 56

Question 8

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 9

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

Accepted Answer

A) NPV 
B) scenario 
C) averaging 
D) trend analysis 
A) NPV 
B) scenario 
C) averaging 
D) trend analysis

Question 10

The amount of variability of a financial output caused by different inputs can be investigated using

Accepted Answer

A) the NPV function. 
B) a histogram of the NPV. 
C) a tornado graph of NPV. 
D) the value at risk (VAR). 
A) the NPV function. 
B) a histogram of the NPV. 
C) a tornado graph of NPV. 
D) the value at risk (VAR).

Question 11

The random nature of games of chance make them poor candidates for simulation.

Accepted Answer

A) True 
 B)False

Question 12

RISKTARGET is a function that allows us to determine the cumulative probability of a particular value in an output distribution,such as the probability of meeting a due date in manufacturing.

Accepted Answer

A) True 
 B)False

Question 13

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

Accepted Answer

A) True 
 B)False

Question 14

Which @RISK function can be used to find the probability of a particular value in an output distribution?

Accepted Answer

A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKTARGET 
A) RISKMIN 
B) RISKMAX 
C) RISKPERCENTILE 
D) RISKTARGET

Question 15

Which of the following is typically not an application of simulation models?

Accepted Answer

A) Operations models 
B) Financial models 
C) Marketing models 
D) Value of information models 
A) Operations models 
B) Financial models 
C) Marketing models 
D) Value of information models

Question 16

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

Accepted Answer

A) value at risk (VAR). 
B) net present value (NPV). 
C) amount of loans required to maintain a minimum cash balance. 
D) interest on loans taken out by a firm. 
A) value at risk (VAR). 
B) net present value (NPV). 
C) amount of loans required to maintain a minimum cash balance. 
D) interest on loans taken out by a firm.

Question 17

Uncertain timing and the events that follow in process modeling can be modeled using IF statements.

Accepted Answer

A) True 
 B)False

Question 18

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

Accepted Answer

A) True 
 B)False

Question 19

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 20

Customer loyalty models are an example of which category of simulation application?

Accepted Answer

A) Operations models 
B) Financial models 
C) Marketing models 
D) Games of chance 
A) Operations models 
B) Financial models 
C) Marketing models 
D) Games of chance

If the warranty period were reduced to 2 years,how much per year in replacement costs would be saved?

RISKMAX and RISKMIN are can be used to find the probability of meeting a given due date in a manufacturing model.

What is an example of a financial application in which simulation cannot be applied?

A key input variable in many marketing models of customer loyalty is the

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

Bidding for contracts is an example of which category of simulation model application?

What is the probability that your portfolio's annual return will exceed 20%?

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 investment models,a useful approach for generating future returns and inflation factors from historical data is the _____ approach.

The amount of variability of a financial output caused by different inputs can be investigated using

The random nature of games of chance make them poor candidates for simulation.

RISKTARGET is a function that allows us to determine the cumulative probability of a particular value in an output distribution,such as the probability of meeting a due date in manufacturing.

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

Which @RISK function can be used to find the probability of a particular value in an output distribution?

Which of the following is typically not an application of simulation models?

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

Uncertain timing and the events that follow in process modeling can be modeled using IF statements.

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

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

Customer loyalty models are an example of which category of simulation application?

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability 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

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 16: Simulation Models

If the warranty period were reduced to 2 years,how much per year in replacement costs would be saved?

RISKMAX and RISKMIN are can be used to find the probability of meeting a given due date in a manufacturing model.

What is an example of a financial application in which simulation cannot be applied?

A key input variable in many marketing models of customer loyalty is the

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

Bidding for contracts is an example of which category of simulation model application?

What is the probability that your portfolio's annual return will exceed 20%?

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 investment models,a useful approach for generating future returns and inflation factors from historical data is the _____ approach.

The amount of variability of a financial output caused by different inputs can be investigated using

The random nature of games of chance make them poor candidates for simulation.

RISKTARGET is a function that allows us to determine the cumulative probability of a particular value in an output distribution,such as the probability of meeting a due date in manufacturing.

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

Which @RISK function can be used to find the probability of a particular value in an output distribution?

Which of the following is typically not an application of simulation models?

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

Uncertain timing and the events that follow in process modeling can be modeled using IF statements.

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

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

Customer loyalty models are an example of which category of simulation application?

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability 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

Analysis of Variance and Experimental Design

Statistical Process Control

Filters