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Test Bank For Business Analytics 3rd Edition By Evans All Chapters 1-16

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Test Bank For Business Analytics 3rd Edition By Evans All Chapters 1-16 t Bank - Table of Contents Chapter 1: Introduction to Business Analytics 1 Chapter 1: Appendix A1 Basic Excel Skills 16 Chapter 2: Database Analytics 24 Chapter 3: Data Visualization 37 Chapter 4: Descriptive Statistics 50 Chapter 5: Probability Distributions and Data Modeling 92 Chapter 6: Sampling and Estimation 108 Chapter 7: Statistical Inference 127 Chapter 8: Trendlines and Regression Analysis 145 Chapter 9: Forecasting Techniques 163 Chapter 10: Introduction to Data Mining 184 Chapter 11: Spreadsheet Modeling and Analysis 198 Chapter 12: Simulation and Risk Analysis 223 Chapter 13: Linear Optimization 237 Chapter 14: Integer and Nonlinear Optimization Models 260 Chapter 15: Optimization Analytics 295 Chapter 16: Decision Analysis 313

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Business Analytics 3rd Edition Evans Test Bank



Test Bank - Table of Contents



Chapter 1: Introduction to Business Analytics 1
Chapter 1: Appendix A1 Basic Excel Skills 16
Chapter 2: Database Analytics 24
Chapter 3: Data Visualization 37
Chapter 4: Descriptive Statistics 50
Chapter 5: Probability Distributions and Data Modeling 92
Chapter 6: Sampling and Estimation 108
Chapter 7: Statistical Inference 127
Chapter 8: Trendlines and Regression Analysis 145
Chapter 9: Forecasting Techniques 163
Chapter 10: Introduction to Data Mining 184
Chapter 11: Spreadsheet Modeling and Analysis 198
Chapter 12: Simulation and Risk Analysis 223
Chapter 13: Linear Optimization 237
Chapter 14: Integer and Nonlinear Optimization Models 260
Chapter 15: Optimization Analytics 295
Chapter 16: Decision Analysis 313




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,Chapter 1: Introduction to Business Analytics

1) Descriptive analytics:
A) can predict risk and find relationships in data not readily apparent with traditional analyses.
B) helps companies classify their customers into segments to develop specific marketing
campaigns.
C) helps detect hidden patterns in large quantities of data to group data into sets to predict
behavior.
D) can use mathematical techniques with optimization to make decisions that take into account
the uncertainty in the data.
Answer: B
Diff: 1
Blooms: Remember
Topic: Descriptive, Predictive, and Prescriptive Analytics
LO1: Illustrate examples of descriptive, predictive, and prescriptive analytics.


2) A manager at Gampco Inc. wishes to know the company's revenue and profit in its previous
quarter. Which of the following business analytics will help the manager?
A) prescriptive analytics
B) normative analytics
C) descriptive analytics
D) predictive analytics
Answer: C
Diff: 1
Blooms: Apply
AACSB: Analytic Skills
Topic: Descriptive, Predictive, and Prescriptive Analytics
LO1: Explain the difference between descriptive, predictive, and prescriptive analytics.


3) Predictive analytics:
A) summarizes data into meaningful charts and reports that can be standardized or customized.
B) identifies the best alternatives to minimize or maximize an objective.
C) uses data to determine a course of action to be executed in a given situation.
D) detects patterns in historical data and extrapolates them forward in time.
Answer: D
Diff: 2
Blooms: Remember
Topic: Descriptive, Predictive, and Prescriptive Analytics
LO1: Illustrate examples of descriptive, predictive, and prescriptive analytics.




1

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,Chapter 1: Introduction to Business Analytics Business Analytics, 3e 11


4) A trader who wants to predict short-term movements in stock prices is likely to use
analytics.
A) predictive
B) descriptive
C) normative
D) prescriptive
Answer: A
Diff: 1
Blooms: Apply
AACSB: Analytic Skills
Topic: Descriptive, Predictive, and Prescriptive Analytics
LO1: Explain the difference between descriptive, predictive, and prescriptive analytics.


5) Which of the following questions will prescriptive analytics help a company address?
A) How many and what types of complaints did they resolve?
B) What is the best way of shipping goods from their factories to minimize costs?
C) What do they expect to pay for fuel over the next several months?
D) What will happen if demand falls by 10% or if supplier prices go up 5%?
Answer: B
Diff: 2
Blooms: Understand
AACSB: Analytic Skills
Topic: Descriptive, Predictive, and Prescriptive Analytics
LO1: Illustrate examples of descriptive, predictive, and prescriptive analytics.


6) The demand for coffee beans over a period of three months has been represented in the form
of an L-shaped curve. Which form of model was used here?
A) mathematical model
B) visual model
C) kinesthetic (tactile) model
D) verbal model
Answer: B
Diff: 1
Blooms: Apply
AACSB: Analytic Skills
Topic: Models in Business Analytics
LO1: Explain the concept of a model and various ways a model can be characterized.


7) Decision variables:
A) cannot be directly controlled by the decision maker.
B) are assumed to be constant.
C) are always uncertain.
D) can be selected at the discretion of the decision maker.




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, 2 Chapter 1 Introduction to Business Analytics Business Analytics, 3e


Answer: D
Diff: 2
Blooms: Understand
Topic: Models in Business Analytics
LO1: Define and list the elements of a decision model.

8) Identify the uncontrollable variable from the following inputs of a decision model.
A) investment returns
B) machine capacities
C) staffing levels
D) intercity distances
Answer: A
Diff: 1
Blooms: Apply
Topic: Models in Business Analytics
LO1: Define and list the elements of a decision model.


9) Which of the following inputs of a decision model is an example of data?
A) estimated consumer demand
B) inflation rates
C) costs
D) investment allocations
Answer: C
Diff: 1
Blooms: Remember
Topic: Data for Business Analytics
LO1: Define and list the elements of a decision model.


10) Descriptive decision models:
A) aim to predict what will happen in the future.
B) describe relationships but do not tell a manager what to do.
C) help analyze the risks associated with various decisions.
D) do not facilitate evaluation of different decisions.
Answer: B
Diff: 2
Blooms: Understand
Topic: Models in Business Analytics
LO1: Explain the concept of a model and various ways a model can be characterized.


11) Prescriptive decision models help:
A) make predictions of how demand is influenced by price.
B) make trade-offs between greater rewards and risks of potential losses.
C) decision makers identify the best solution to decision problems.




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