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Solutions Manual – Introduction to Business Analytics, 2026 Release by Vernon J. Richardson

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Build confidence in business analytics and problem-solving with this Solutions Manual for Introduction to Business Analytics, 2026 Release by Vernon J. Richardson and Marcia Weidenmier Watson. ISBN13: 9781265680978. This resource includes End-of-Chapter Assignment Solutions, MCQs, Discussion Questions & Problems Solutions, and Lab Solutions, providing comprehensive support for reviewing key concepts, completing assignments, solving problems, and working through analytics labs. The complete table of contents is provided below for easy reference. Ideal for assignments, exam preparation, self-study, and instructor support. 1. Specify the Question: Using Business Analytics to Address Business Questions 2. Obtain the Data: Data Sources and Data Preparation 3. Analyze the Data: Basic Statistics and Tools Required in Business Analytics 4. Analyze the Data: Descriptive Analytics and Diagnostic Analytics 5. Analyze the Data: Predictive Analytics and Prescriptive Analytics 6. Report the Results: Using Data Visualization 7. Marketing Analytics 8. Accounting Analytics 9. Financial Analytics 10. Human Resources, IT, Operations, and Supply Chain Analytics 11. Artificial Intelligence (AI) 12. Using the SOAR Analytics Model to Put It All Together: Three Capstone Projects

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SOLUTIONS MANUAL




** All Chapters included
** End-of-Chapter Assignment Solutions
** MCQs, Discussion QAs & Problems Solutions
** Lab Solutions

,Table of Contents are given below


1. Specify the Question: Using Business Analytics to Address Business Questions

2. Obtain the Data: Data Sources and Data Preparation

3. Analyze the Data: Basic Statistics and Tools Required in Business Analytics

4. Analyze the Data: Descriptive Analytics and Diagnostic Analytics

5. Analyze the Data: Predictive Analytics and Prescriptive Analytics

6. Report the Results: Using Data Visualization

7. Marketing Analytics

8. Accounting Analytics

9. Financial Analytics

10. Human Resources, IT, Operations, and Supply Chain Analytics

11. Artificial Intelligence (AI)

12. Using the SOAR Analytics Model to Put It All Together: Three Capstone

Projects

, Richardson and Watson—Introduction to Business Analytics, 2026 Release—Chapter 1



Chapter 1 End-of-Chapter Assignment Solutions
Multiple Choice Questions

1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to
accomplish a specific business task is called a:
a. business processes.
b. business analysis.
c. business procedure.
d. business value.

2. (LO 1.2) According to the information value chain, data combined with context is:
a. Information.
b. Knowledge.
c. Insight.
d. Value.

3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate
results to the decision maker?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results

4. (LO 1.5) Which phase of the SOAR analytics model involves finding the most appropriate data
needed to address the business question?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results

5. (LO 1.5) Which questions seek information about Tesla’s sales in the next quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can
we forecast what will happen?
d. What should we do, based on what we expect will happen? How do we optimize our
performance based on potential constraints?

6. (LO 1.5) Which questions seek information on the routing of products from Queretaro, Mexico to
Chicago, United States in the last quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we
forecast what will happen?
d. What should we do, based on what we expect will happen? How do we optimize our
performance based on potential constraints?




1

, Richardson and Watson—Introduction to Business Analytics, 2026 Release—Chapter 1


7. (LO 1.5) Which questions ask why net income is increasing when revenues are decreasing,
counter to expectations?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we
forecast what will happen?
d. What should we do, based on what we expect will happen? How do we optimize our
performance based on potential constraints?

8. (LO 1.5) Which questions help managers understand how to organize future shipments based on
expected demand?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we
forecast what will happen?
d. What should we do, based on what we expect will happen? How do we optimize our
performance based on potential constraints?

9. (LO 1.5) Which term refers to the combined accuracy, validity, and consistency of data stored
and used over time?
a. Data integrity
b. Data overload
c. Data value
d. Information value

10. (LO 1.3) A specialist who knows how to work with, manipulate, and statistically test data is a:
a. decision maker.
b. data scientist.
c. data analyst.
d. decision scientist.

11. (LO 1.4) Which type of analysts predicts the amount of money that a company will receive from
its customers to help management evaluate future investments based on expected investment
performance, such as investments in equipment or employee training?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst

12. (LO 1.4) Which type of analyst addresses questions regarding tax and auditing?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst

13. (LO 1.5) Suppose a company has timely product reviews that are available when needed, but the
reviews are biased. These product reviews are which type of data?
a. Reliable
b. Relevant
c. Curated



2

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