Question 1

We typically choose between a symmetric and skewed distribution on the basis of realism.

Accepted Answer

A) True 
 B)False

Question 2

Which of the following statements is correct regarding the graph of a discrete probability distribution?

Accepted Answer

A)  It is a series of spikes. 
B)  The height of each spike is the probability of the corresponding value. 
C)  There is an empty space between adjacent spikes. 
D)  All of these statements are correct. 
A)  It is a series of spikes. 
B)  The height of each spike is the probability of the corresponding value. 
C)  There is an empty space between adjacent spikes. 
D)  All of these statements are correct.

Question 3

A common guideline in constructing confidence intervals for the mean is to place upper and lower bounds one standard error on either side of the average to obtain an approximate 95% confidence interval.

Accepted Answer

A) True 
 B)False

Question 4

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 5

In August 2017, a car dealer is trying to determine how many 2018 cars to order. Each car ordered in August 2017 costs $16,000. The demand for the dealer's 2018 models has the probability distribution shown in the table below. Each car sells for $21,000. If the demand for 2018 cars exceeds the number of cars ordered in August 2017, the dealer must reorder at a cost of $18,000 per car. Excess cars can be disposed of at $13,000 per car.
​  
-(A) Use simulation to determine how many cars the dealer should order in August, 2017 to maximize his expected profit.
​
(B) For the optimal order quantity, find a 95% confidence interval for the expected profit.
​
(C) Why is it important to develop the confidence interval in (B)?

Accepted Answer

(A) Summary measures from simulation wit

Question 6

The binomial distribution can be well approximated by the normal distribution when the number of trials n is sufficiently small and the probability of success p is not too close to 0 or 1.

Accepted Answer

A) True 
 B)False

Question 7

A probability distribution is bounded if there are values A and B such that:

Accepted Answer

A)  A and B represent the 95% confidence interval 
B)  A and B are the mean and standard deviation, respectively 
C)  A and B are the mean and variance, respectively 
D)  no value can be less than A or greater than B 
A)  A and B represent the 95% confidence interval 
B)  A and B are the mean and standard deviation, respectively 
C)  A and B are the mean and variance, respectively 
D)  no value can be less than A or greater than B

Question 8

Sometimes it is convenient to treat a discrete probability distribution as continuous, and vice versa.

Accepted Answer

A) True 
 B)False

Question 9

RISKSIMTABLE is a function in @RISK for running several simulations simultaneously, one for each setting of an input or decision variable.

Accepted Answer

A) True 
 B)False

Question 10

Obtain another set random numbers by pressing the F9 (recalculate) key. Do your results change significantly? Do the changes match your expectations? Explain your answer.

Accepted Answer

The results will vary from sim

Question 11

@RISK introduces uncertainty explicitly into a spreadsheet model by allowing several inputs to have probability distributions and then enabling the simulation of random values from these inputs.

Accepted Answer

A) True 
 B)False

Question 12

The "building blocks" of all spreadsheet simulation models are:

Accepted Answer

A)  deterministic inputs 
B)  random numbers between 0 and 1 
C)  decision variables 
D)  probability distributions for uncertain input variables 
A)  deterministic inputs 
B)  random numbers between 0 and 1 
C)  decision variables 
D)  probability distributions for uncertain input variables

Question 13

Oregon State University has reached the final four in the 2016 NCAA Women's Basketball Tournament, and as a result, a sweatshirt supplier in Corvallis is trying to decide how many sweatshirts to print for the upcoming championships. The final four teams (Oregon State, University of Washington, Syracuse, and University of Connecticut) have emerged from the quarterfinal round, and there is a week left until the semifinals, which are then followed in a couple of days by the finals. Each sweatshirt costs $12 to produce and sells for $24. However, in three weeks, any leftover sweatshirts will be put on sale for half price, $12. The supplier assumes that the demand (in thousands) for his sweatshirts during the next three weeks, when interest is at its highest, follows the probability distribution shown in the table below. The residual demand, after the sweatshirts have been put on sale, also has the probability distribution shown in the table below. The supplier realizes that every sweatshirt sold, even at the sale price, yields a profit. However, he also realizes that any sweatshirts produced but not sold must be thrown away, resulting in a $12 loss per sweatshirt.
​
Demand distribution at regular price Demand distribution at reduced price
​  
-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 14

(A) What fraction of the random numbers are smaller than 0.5?
​
(B) What fraction of the time is a random number less than 0.5 followed by another random number less than 0.5?
​
(C) What fraction of the random numbers are larger than 0.8?
​
(D) What do you expect the answers to (A), (B) and (C) to be before simulating? Do the answers you provided to those questions match your expectations? Explain why or why not.
​
(E) Suppose your answers to (A), (B) and (C) are not close to the expected answers. What can you do to obtain answers from the simulation that are closer to the expected answers?

Accepted Answer

​
(A) In the particular sample shown bel

Question 15

Discrete distributions are sometimes used as approximations of continuous distributions:

Accepted Answer

A)  because they are more accurate 
B)  because they are simpler 
C)  when the mean and variance of the distribution are unknown 
D)  when the shape of the continuous distribution is not symmetric 
A)  because they are more accurate 
B)  because they are simpler 
C)  when the mean and variance of the distribution are unknown 
D)  when the shape of the continuous distribution is not symmetric

Question 16

Which of the following statements are false regarding the numbers generated by the RAND function in Excel®?

Accepted Answer

A)  Approximately 10% of the numbers will be between 0.0 and 1.0. 
B)  Approximately 20% of the numbers will be between 0.50 and 0.70. 
C)  Approximately 40% of the numbers will be between 0.20 and 0.60. 
D)  Approximately 60% of the numbers will be between 0.15 and 0.75. 
E)  All of these statements are false. 
A)  Approximately 10% of the numbers will be between 0.0 and 1.0. 
B)  Approximately 20% of the numbers will be between 0.50 and 0.70. 
C)  Approximately 40% of the numbers will be between 0.20 and 0.60. 
D)  Approximately 60% of the numbers will be between 0.15 and 0.75. 
E)  All of these statements are false.

Question 17

If we want to model the monthly return on a stock, a good option would be:

Accepted Answer

A)  a symmetric distribution around 0 
B)  a positively skewed distribution 
C)  a negatively skewed distribution 
D)  all of these choices 
A)  a symmetric distribution around 0 
B)  a positively skewed distribution 
C)  a negatively skewed distribution 
D)  all of these choices

Question 18

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 19

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

Accepted Answer

A)  It makes decision-making easier. 
B)  It explicitly incorporates uncertainty in one or more input variables. 
C)  It does not require any best guesses. 
D)  All of these statements are true. 
A)  It makes decision-making easier. 
B)  It explicitly incorporates uncertainty in one or more input variables. 
C)  It does not require any best guesses. 
D)  All of these statements are true.

Question 20

The triangular distribution is sometimes used in simulation models because it is more flexible and intuitive than the normal distribution.

Accepted Answer

A) True 
 B)False

We typically choose between a symmetric and skewed distribution on the basis of realism.

Which of the following statements is correct regarding the graph of a discrete probability distribution?

A common guideline in constructing confidence intervals for the mean is to place upper and lower bounds one standard error on either side of the average to obtain an approximate 95% confidence interval.

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

The binomial distribution can be well approximated by the normal distribution when the number of trials n is sufficiently small and the probability of success p is not too close to 0 or 1.

A probability distribution is bounded if there are values A and B such that:

Sometimes it is convenient to treat a discrete probability distribution as continuous, and vice versa.

RISKSIMTABLE is a function in @RISK for running several simulations simultaneously, one for each setting of an input or decision variable.

Obtain another set random numbers by pressing the F9 (recalculate) key. Do your results change significantly? Do the changes match your expectations? Explain your answer.

@RISK introduces uncertainty explicitly into a spreadsheet model by allowing several inputs to have probability distributions and then enabling the simulation of random values from these inputs.

The "building blocks" of all spreadsheet simulation models are:

Discrete distributions are sometimes used as approximations of continuous distributions:

Which of the following statements are false regarding the numbers generated by the RAND function in Excel^®?

If we want to model the monthly return on a stock, a good option would be:

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/are true regarding a simulation model?

The triangular distribution is sometimes used in simulation models because it is more flexible and intuitive than the normal distribution.

Introduction to Business Analytics

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

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 15: Introduction to Simulation Modeling

We typically choose between a symmetric and skewed distribution on the basis of realism.

Which of the following statements is correct regarding the graph of a discrete probability distribution?

A common guideline in constructing confidence intervals for the mean is to place upper and lower bounds one standard error on either side of the average to obtain an approximate 95% confidence interval.

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

The binomial distribution can be well approximated by the normal distribution when the number of trials n is sufficiently small and the probability of success p is not too close to 0 or 1.

A probability distribution is bounded if there are values A and B such that:

Sometimes it is convenient to treat a discrete probability distribution as continuous, and vice versa.

RISKSIMTABLE is a function in @RISK for running several simulations simultaneously, one for each setting of an input or decision variable.

Obtain another set random numbers by pressing the F9 (recalculate) key. Do your results change significantly? Do the changes match your expectations? Explain your answer.

@RISK introduces uncertainty explicitly into a spreadsheet model by allowing several inputs to have probability distributions and then enabling the simulation of random values from these inputs.

The "building blocks" of all spreadsheet simulation models are:

Discrete distributions are sometimes used as approximations of continuous distributions:

Which of the following statements are false regarding the numbers generated by the RAND function in Excel®?

If we want to model the monthly return on a stock, a good option would be:

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/are true regarding a simulation model?

The triangular distribution is sometimes used in simulation models because it is more flexible and intuitive than the normal distribution.

Introduction to Business Analytics

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

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Which of the following statements are false regarding the numbers generated by the RAND function in Excel^®?

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: