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Test Bank for Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th Edition (Ramesh Sharda, Dursun Delen & Efraim Turban, 2020) | All Chapters 1–14 Covered

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Complete test bank for Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th Edition by Ramesh Sharda, Dursun Delen, and Efraim Turban (2020), covering business analytics, decision support systems, business intelligence, data science, artificial intelligence, predictive and prescriptive analytics, machine learning, deep learning, text mining, big data, robotics, collaborative systems, knowledge systems, the Internet of Things, and the ethical and societal implications of analytics and AI. The test bank includes Chapter 1 An Overview of Business Analytics, Decision Support Systems, Business Intelligence, Data Science, and Artificial Intelligence; Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications; Chapter 3 Nature of Data, Statistical Modeling, and Visualization; Chapter 4 Data Mining Process, Methods, and Applications; Chapter 5 Machine Learning Techniques for Predictive Analytics; Chapter 6 Deep Learning and Cognitive Computing; Chapter 7 Text Mining, Sentiment Analysis, and Social Analytics; Chapter 8 Prescriptive Analytics with Optimization and Simulation; Chapter 9 Big Data, Location Analytics, and Cloud Computing; Chapter 10 Robotics: Industrial and Consumer Applications; Chapter 11 Group Decision Making, Collaborative Systems, and AI Support; Chapter 12 Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors; Chapter 13 The Internet of Things as a Platform for Intelligent Applications; and Chapter 14 Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts, providing comprehensive chapter-based assessments and exam preparation for business analytics, data science, artificial intelligence, information systems, and decision-support courses.

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, TABLE OF CONTENTS
Test Bank for Analytics, Data Science, & Artificial Intelligence: Systems for
Decision Support, 11th Edition
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Authors: Ramesh Sharda, Dursun Delen, and Efraim Turban


PART I: INTRODUCTION TO ANALYTICS AND AI
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Chapter 1. An Overview of Business Analytics, Decision Support Systems, Business Intelligence, Data
Science, and Artificial Intelligence
Chapter 2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications




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Chapter 3. Nature of Data, Statistical Modeling, and Visualization
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PART II: PREDICTIVE ANALYTICS AND MACHINE LEARNING




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Chapter 4. Data Mining Process, Methods, and Applications
Chapter 5. Machine Learning Techniques for Predictive Analytics
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Chapter 6. Deep Learning and Cognitive Computing
Chapter 7. Text Mining, Sentiment Analysis, and Social Analytics
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PART III: PRESCRIPTIVE ANALYTICS AND BIG DATA
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Chapter 8. Prescriptive Analytics with Optimization and Simulation
Chapter 9. Big Data, Location Analytics, and Cloud Computing
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PART IV: ROBOTICS, SOCIAL NETWORKS, AI, AND IOT
Chapter 10. Robotics: Industrial and Consumer Applications
PR

Chapter 11. Group Decision Making, Collaborative Systems, and AI Support
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Chapter 12. Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal
Assistants, and Robo Advisors
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Chapter 13. The Internet of Things As a Platform for Intelligent Applications
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PART V: CAVEATS OF ANALYTICS AND AI
Chapter 14. Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts
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, Analytics, Data Science, & Artificial Intelligence, 11e (Sharda)
Chapter 1 Overview of Business Intelligence, Analytics, Data Science, and Artificial
Intelligence: Systems for Decision Support
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1) In the opening case KONE has minimized downtime and shortened the repair time.
Answer: TRUE
Diff: 2 Page Ref: 4
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2) Intelligent technologies are limited to small-scale projects when they include AI combined
with IoT.
Answer: FALSE
Diff: 2 Page Ref: 5
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3) Decision making is one of the most important activities in organizations of all kind– probably
the most important one.
Answer: TRUE
Diff: 1 Page Ref: 5
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4) Managers historically considered decision making purely a science.
Answer: FALSE
Diff: 1 Page Ref: 6
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5) With more data and analysis technologies, more alternatives can be evaluated, forecasts can be
improved, risk analysis can be performed quickly, and the views of experts can be collected
quickly and at a reduced cost.
Answer: TRUE
Diff: 2 Page Ref: 8
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6) It is generally best to rely on a trial-and-error approach to management.
Answer: FALSE
Diff: 2 Page Ref: 7
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7) A major characteristic of computerized decision support and many BI tools (notably those of
business analytics) is the inclusion of at least one model.
Answer: TRUE
Diff: 2 Page Ref: 13

8) The definition of implementation is straightforward because implementation is a simple, direct
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process with defined boundaries.
Answer: FALSE
Diff: 2 Page Ref: 13

9) Structured problems are encountered in only unique situations.
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Answer: FALSE
Diff: 3 Page Ref: 16


1
Copyright © 2020 Pearson Education, Inc.

, 10) Unstructured problems can be fully supported by standard computerized quantitative
methods.
Answer: FALSE
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Diff: 3 Page Ref: 16

11) During the 1990s, the primary focus of information systems support for decision making
focused on providing structured, periodic reports that a manager could use for decision making.
Answer: FALSE
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Diff: 3 Page Ref: 22

12) Decision support systems couple the intellectual resources of individuals with the capabilities
of the computer to improve the quality of decisions. It is a computer-based support system for
management decision makers who deal with semistructured problems.
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Answer: TRUE
Diff: 2 Page Ref: 22

13) The term decision support system is a very specific term that implies the same tool, system,
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and development approach to most developers.
Answer: FALSE
Diff: 3 Page Ref: 23

14) BI systems rely on a DW as the information source for creating insight and supporting
AP
managerial decisions.
Answer: TRUE
Diff: 2 Page Ref: 27

15) One of the four components of BI systems, business performance management, is a
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collection of source data in the data warehouse.
Answer: FALSE
Diff: 3 Page Ref: 25

16) Analytics is the process of developing actionable decisions or recommendations for actions
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based on insights generated from historical data.
Answer: TRUE
Diff: 3 Page Ref: 31

17) The use of dashboards and data visualizations is seldom effective in finding efficiencies in
organizations, as demonstrated by the Seattle Children's Hospital Case Study.
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Answer: FALSE
Diff: 2 Page Ref: 32

18) The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball
book, is an example of the effectiveness of prescriptive analytics.
??
Answer: TRUE
Diff: 2 Page Ref: 39


2
Copyright © 2020 Pearson Education, Inc.

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Subido en
12 de agosto de 2026
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