SOLUTIONS MANUAL
Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Business
Analytics, 9th edition
by Cliff Ragsdale
LU
XE
LI
BR
AR
Y
,LU
All Chapters/ Excel
Supplement files
XE
download link at the end
of this file.
LI
BR
AR
Y
, TABLE OF CONTENT
Chapter 1. Introduction to Modeling and Decision Analysis
Chapter 2. Introduction to Optimization and Linear Programming
Chapter 3. Modeling and Solving LP Problems in a Spreadsheet
Chapter 4. Sensitivity Analysis and the Simplex Method
Chapter 5. Network Modeling
Chapter 6. Integer Linear Programming
LU
Chapter 7. Goal Programming and Multiple Objective Optimization
Chapter 8. Nonlinear Programming and Evolutionary Optimization
Chapter 9. Regression Analysis
Chapter 10. Data Mining
XE
Chapter 11. Time Series Forecasting
Chapter 12. Introduction to Simulation Using Analytic Solver
Chapter 13. Queuing Theory
Chapter 14. Decision Analysis
LI
Chapter 15. Project Management
BR
AR
Y
, classmerit.com — The Marketplace to Buy and Sell Study Materials
Chapter 1
Introduction to Modeling and Decision Analysis
1. Decision Analysis: Identifying and evaluating the different possible courses of action that might be chosen to
address a decision problem.
2. Computer Model: A set of mathematical relationships and logical assumptions implemented in a computer as a
representation of some real-world object or phenomenon.
LU
3. A spreadsheet model is a type (or special case) of a computer model where a spreadsheet is used to implement
the model.
4. Business Analytics: A field of study that uses computers, statistics, and mathematics to solve business
problems.
5. Many of the tools and techniques from the field of business analytics can be implemented and used in
spreadsheets.
XE
6. Spreadsheets are sometimes used to store lists of data, such as the grades of students in a class, or names,
addresses, and phone numbers of friends and family. These types of “database” applications of spreadsheets do
not fall into the area of business analytics unless the data is being “mined” with a specific objective in mind.
7. Spreadsheets facilitate the decision-making process by making it easier to play out various what-if scenarios.
8. A modeling approach to decision making is beneficial in that the decision maker can analyze the probable
impact of numerous alternative before selecting an alternative for implementation.
LI
9. Dependent Variable: A bottom-line performance measure of interest to the decision maker that is influenced by
other variables in the model; denoted by the symbol Y in the expression Y = (X1, X2, ..., X3).
10. Independent Variable: A variable that influences (or plays a role in determining) the value of some bottom-line
performance measure (dependent variable); denoted by the symbols X i in the expression Y = (X1, X2, ..., X3).
BR
11. Yes, a model can have more than one dependent variable. In some decision problems, a manager might be
interested in evaluating various alternatives on the basis of profit, probable number of injuries, resulting
amount of toxic waste produced, etc. Each of the variables represents a bottom-line performance measure that
the manager might be interested in that should be included in the model.
12. Yes. See the answer to the previous question.
13. Several of the models used in predictions surrounding the COVID-19 pandemic in 2020 turned out to be wrong
but provided useful guidance in actions that saved many lives.
AR
See: https://www.kunc.org/health/2020-04-07/all-models-are-wrong-but-some-are-useful-what-covid-19-
predictions-can-and-cant-tell-us#stream/0
14. The solution to prescriptive models tells managers what actions to take while descriptive models simply
describe the operation of a system. In descriptive models, the values to be assumed by one or more independent
variables are uncertain and not under the decision maker’s control.
15. The solution to prescriptive models tells managers what actions to take while predictive models provide
forecasts of what will happen in the future. In predictive models, the functional form () describing the nature
Y
of the relationship between the dependent and independent variable is ill-defined or not precisely known.
16. Descriptive models have a well-defined functional form, but the values of one or more of the independent
variables are unknown or uncertain. In predictive models, the values of the independent variables are known or
under the decision maker’s control, but the functional form () describing the nature of the relationship
between the dependent and independent variables is ill-defined or not precisely known.
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Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Business
Analytics, 9th edition
by Cliff Ragsdale
LU
XE
LI
BR
AR
Y
,LU
All Chapters/ Excel
Supplement files
XE
download link at the end
of this file.
LI
BR
AR
Y
, TABLE OF CONTENT
Chapter 1. Introduction to Modeling and Decision Analysis
Chapter 2. Introduction to Optimization and Linear Programming
Chapter 3. Modeling and Solving LP Problems in a Spreadsheet
Chapter 4. Sensitivity Analysis and the Simplex Method
Chapter 5. Network Modeling
Chapter 6. Integer Linear Programming
LU
Chapter 7. Goal Programming and Multiple Objective Optimization
Chapter 8. Nonlinear Programming and Evolutionary Optimization
Chapter 9. Regression Analysis
Chapter 10. Data Mining
XE
Chapter 11. Time Series Forecasting
Chapter 12. Introduction to Simulation Using Analytic Solver
Chapter 13. Queuing Theory
Chapter 14. Decision Analysis
LI
Chapter 15. Project Management
BR
AR
Y
, classmerit.com — The Marketplace to Buy and Sell Study Materials
Chapter 1
Introduction to Modeling and Decision Analysis
1. Decision Analysis: Identifying and evaluating the different possible courses of action that might be chosen to
address a decision problem.
2. Computer Model: A set of mathematical relationships and logical assumptions implemented in a computer as a
representation of some real-world object or phenomenon.
LU
3. A spreadsheet model is a type (or special case) of a computer model where a spreadsheet is used to implement
the model.
4. Business Analytics: A field of study that uses computers, statistics, and mathematics to solve business
problems.
5. Many of the tools and techniques from the field of business analytics can be implemented and used in
spreadsheets.
XE
6. Spreadsheets are sometimes used to store lists of data, such as the grades of students in a class, or names,
addresses, and phone numbers of friends and family. These types of “database” applications of spreadsheets do
not fall into the area of business analytics unless the data is being “mined” with a specific objective in mind.
7. Spreadsheets facilitate the decision-making process by making it easier to play out various what-if scenarios.
8. A modeling approach to decision making is beneficial in that the decision maker can analyze the probable
impact of numerous alternative before selecting an alternative for implementation.
LI
9. Dependent Variable: A bottom-line performance measure of interest to the decision maker that is influenced by
other variables in the model; denoted by the symbol Y in the expression Y = (X1, X2, ..., X3).
10. Independent Variable: A variable that influences (or plays a role in determining) the value of some bottom-line
performance measure (dependent variable); denoted by the symbols X i in the expression Y = (X1, X2, ..., X3).
BR
11. Yes, a model can have more than one dependent variable. In some decision problems, a manager might be
interested in evaluating various alternatives on the basis of profit, probable number of injuries, resulting
amount of toxic waste produced, etc. Each of the variables represents a bottom-line performance measure that
the manager might be interested in that should be included in the model.
12. Yes. See the answer to the previous question.
13. Several of the models used in predictions surrounding the COVID-19 pandemic in 2020 turned out to be wrong
but provided useful guidance in actions that saved many lives.
AR
See: https://www.kunc.org/health/2020-04-07/all-models-are-wrong-but-some-are-useful-what-covid-19-
predictions-can-and-cant-tell-us#stream/0
14. The solution to prescriptive models tells managers what actions to take while descriptive models simply
describe the operation of a system. In descriptive models, the values to be assumed by one or more independent
variables are uncertain and not under the decision maker’s control.
15. The solution to prescriptive models tells managers what actions to take while predictive models provide
forecasts of what will happen in the future. In predictive models, the functional form () describing the nature
Y
of the relationship between the dependent and independent variable is ill-defined or not precisely known.
16. Descriptive models have a well-defined functional form, but the values of one or more of the independent
variables are unknown or uncertain. In predictive models, the values of the independent variables are known or
under the decision maker’s control, but the functional form () describing the nature of the relationship
between the dependent and independent variables is ill-defined or not precisely known.
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