Solution Manual for Introduction to Business Analytics, 1st Edition By Vernon Richardson and Marcia Watson Verified Chapter's 1 - 12 | Complete

Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions


Solution Manual for Introduction to Business Analytics,
1st Edition
By Vernon Richardson and Marcia Watson
Verified Chapter's 1 - 12 | Complete

, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions




TABLE OF CONTENTS
Chapter 1: Specify the Question: Using Business Analytics to Address Business Questions

Chapter 2: Obtain the Data: An Introduction to Business Data Sources

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

Chapter 4: Analyze the Data: Exploratory Business Analytics (Descriptive Analytics and Diagnostic Analytics)

Chapter 5: Analyze the Data: Confirmatory Business Analytics (Predictive Analytics and Prescriptive Analytics)

Chapter 6: Report the Results: Using Data Visualization

Chapter 7: Marketing Analytics

Chapter 8: Accounting Analytics

Chapter 9: Financial Analytics

Chapter 10: Operations Analytics

Chapter 11: Advanced Business Analytics

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

, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions



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. 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?

, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
7. (LO 1.5) Which dquestions dask dwhy dnet dincome dis dincreasing dwhen drevenues dare ddecreasing,
dcounter dtodexpectations?
a. What dhappened? dWhat dis dhappening?
b. Why ddid dit dhappen? dWhat dare dthe dcauses dof dpast dresults?
c. Will dit dhappen din dthe dfuture? dWhat dis dthe dprobability dsomething dwill dhappen? dCan dwe
dforecast dwhat dwilldhappen?
d. What dshould dwe ddo, dbased don dwhat dwe dexpect dwill dhappen? dHow ddo dwe doptimize dour
dperformance dbaseddon dpotential dconstraints?

8. (LO d1.5) dWhich dquestions dhelp dmanagers dunderstand dhow dto dorganize dfuture dshipments dbased
don dexpectedddemand?
a. What dhappened? dWhat dis dhappening?
b. Why ddid dit dhappen? dWhat dare dthe dcauses dof dpast dresults?
c. Will dit dhappen din dthe dfuture? dWhat dis dthe dprobability dsomething dwill dhappen? dCan dwe
dforecast dwhat dwilldhappen?
d. What dshould dwe ddo, dbased don dwhat dwe dexpect dwill dhappen? dHow ddo dwe doptimize dour
dperformancedbased don dpotential dconstraints?

9. (LO d1.5) dWhich dterm drefers dto dthe dcombined daccuracy, dvalidity, dand dconsistency dof ddata dstored
dand dused doverdtime?
a. Data dintegrity
b. Data doverload
c. Data dvalue
d. Information dvalue

10. (LO d1.3) dA dspecialist dwho dknows dhow dto dwork dwith, dmanipulate, dand dstatistically dtest ddata dis da
a. decision dmaker.
b. data dscientist.
c. data danalyst.
d. decision dscientist.

11. (LO d1.4) dWhich dtype dof danalysts dpredicts dthe damount dof dmoney dthat da dcompany dwill dreceive dfrom dits
dcustomers dtodhelp dmanagement devaluate dfuture dinvestments dbased don dexpected dinvestment
dperformance, dsuch das dinvestments din dequipment dor demployee dtraining?
a. Marketing danalyst
b. Operations danalyst
c. Financial danalyst
d. Accounting danalyst

12. (LO d1.4) dWhich dtype dof danalyst daddresses dquestions dregarding dtax dand dauditing?
a. Marketing danalyst
b. Operations danalyst
c. Financial danalyst
d. Accounting danalyst

13. (LO d1.5) dSuppose da dcompany dhas dtimely dproduct dreviews dthat dare davailable dwhen dneeded, dbut dthe
dreviews daredbiased. dThese dproduct dreviews dare dwhich dtype dof ddata?
a. Reliable
b. Relevant
c. Curated
d. Consistent
© dMcGraw dHill dLLC. dAll drights dreserved. dNo dreproduction dor ddistribution dwithout dthe dprior dwritten dconsent dof dMcGraw dHill
dLLC.


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