© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
1
, Introduction kto kBusiness kAnalytics k1st kEdition kVernon kJ. kRichardson
kMarcia kWeidenmier kWatson
Chapter k1 kEnd-of-Chapter kAssignment kSolutions
Multiple kChoice kQuestions
1. (LO k1.1) kA kcoordinated, kstandardized kset kof kactivities kconducted kby kboth kpeople kand kequipment kto
kaccomplish ka kspecific kbusiness ktask kis kcalled k .
a. business kprocesses
b. business kanalysis
c. business kprocedure
d. business kvalue
2. (LO k1.2) kAccording kto kthe kinformation kvalue kchain, kdata kcombined kwith kcontext kis
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO k1.5) kWhich kphase kof kthe kSOAR kanalytics kmodel kaddresses kthe kproper kway kto kcommunicate
kresults kto kthe kdecision kmaker?
a. Specify kthe kquestion
b. Obtain kthe kdata
c. Analyze kthe kdata
d. Report kthe kresults
4. (LO k1.5) kWhich kphase kof kthe kSOAR kanalytics kmodel kinvolves kfinding kthe kmost kappropriate kdata kneeded
kto kaddress kthe kbusiness kquestion?
a. Specify kthe kquestion
b. Obtain kthe kdata
c. Analyze kthe kdata
d. Report kthe kresults
5. (LO k1.5) kWhich kquestions kseek kinformation kabout kTesla’s ksales kin kthe knext kquarter?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe
kforecast kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
2
, Chapter k01 k– kSpecify kthe kQuestion: kUsing kBusiness kAnalytics kto kAddress kBusiness kQuestions
6. (LO k1.5) kWhich kquestions kseek kinformation kon kthe krouting kof kproducts kfrom kQueretaro, kMexico kto
kChicago, kUnited kStates kin kthe klast kquarter?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
7. (LO k1.5) kWhich kquestions kask kwhy knet kincome kis kincreasing kwhen krevenues kare kdecreasing,
kcounter kto kexpectations?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
8. (LO k1.5) kWhich kquestions khelp kmanagers kunderstand khow kto korganize kfuture kshipments kbased kon
kexpected kdemand?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
9. (LO k1.5) kWhich kterm krefers kto kthe kcombined kaccuracy, kvalidity, kand kconsistency kof kdata kstored kand
kused kover ktime?
a. Data kintegrity
b. Data koverload
c. Data kvalue
d. Information kvalue
10. (LO k1.3) kA kspecialist kwho kknows khow kto kwork kwith, kmanipulate, kand kstatistically ktest kdata kis ka
a. decision kmaker.
b. data kscientist.
c. data kanalyst.
d. decision kscientist.
11. (LO k1.4) kWhich ktype kof kanalysts kpredicts kthe kamount kof kmoney kthat ka kcompany kwill kreceive kfrom kits
kcustomers kto khelp kmanagement kevaluate kfuture kinvestments kbased kon kexpected kinvestment
kperformance, ksuch kas kinvestments kin kequipment kor kemployee ktraining?
a. Marketing kanalyst
b. Operations kanalyst
c. Financial kanalyst
d. Accounting kanalyst
12. (LO k1.4) kWhich ktype kof kanalyst kaddresses kquestions kregarding ktax kand kauditing?
a. Marketing kanalyst
b. Operations kanalyst
© kMcGraw kHill kLLC. kAll krights kreserved. kNo kreproduction kor kdistribution kwithout kthe kprior kwritten kconsent kof kMcGraw kHill
kLLC.
3
, c. Financial kanalyst
d. Accounting kanalyst
13. (LO k1.5) kSuppose ka kcompany khas ktimely kproduct kreviews kthat kare kavailable kwhen kneeded, kbut kthe
kreviews kare kbiased. kThese kproduct kreviews kare kwhich ktype kof kdata?
a. Reliable
b. Relevant
c. Curated
d. Consistent
14. (LO k1.6) kWhich kcommon kvisualization ktype kshows ktrends kin kvalues kover ktime?
a. Line kgraph
b. Scatterplot
c. Pie kchart
d. Bar kchart
15. (LO k1.6) kWhich kcommon kvisualization ktype kshows kthe kcomposition kof kvalues kover ktime?
a. Line kgraph
b. Scatterplot
c. Pie kchart
d. Bar kchart
Discussion kQuestions
1. (LO k1.1) kGive kfive kexamples kof kbusiness kprocesses kat kTesla. k How kdo kthey kcreate kbusiness kvalue kfor
kTesla kand kits kshareholders?
Suggested kSolution:
Answers kwill kvary,
1. Tesla kprocures kautomobile kparts kfrom kauto ksuppliers k– Because kof kTesla’s kunique kstyling, kgetting
kquality kparts kfrom kits ksuppliers kon ka ktimely kbasis kwill ksupport kits kmanufacturing kbusiness.
2. Tesla kmanufactures kbatteries kfor kits kelectric kvehicle kat kits kdesired kspecifications k– kThe kquantity
kand kquality kof kits kbatteries kare kof kcritical kimportance kto kTesla.
3. Accepting kand kprocessing kpreorders kfrom kits kcustomers k– kTesla kreceives ksome kindication kof kthe
kdemand kfor keach kof kits kproducts, kthat khelps kwith kplanning.
4. Tesla kmarkets kits kproducts k– kTesla kworks kto kget kTesla kproducts kin kthe kfront kof kmind kfor kits
kcustomers.
5. Tesla kcar kand ktruck kdesign k– kTesla kdesigns kits kautomobiles kin ka kway kthat kwill kappeal kto kits
kcustomers k(for kexample, kCybertruck).
2. (LO k1.2) kExplain kthe kinformation kvalue kchain kby ksummarizing khow kdata kare ktransformed kinto
kknowledge kinsights kfor kdecision-making. kUse kthe kexample kof ka kbook kreview kon kAmazon kand khow kit
kmight klead kAmazon kto kdecide khow kmany kof kthose kbooks kto kstock kat kits kwarehouses.
Suggested kSolution:
Amazon kallows kthose kwho kpurchase kbooks kand kother kproducts kat kits kwebsite kto kgive kproduct kreviews
kand kassign kproduct kratings. k The kproduct kreviews kmay kprovide ktext kwhich ktextual kanalytics kcould kuse
kto kunderstand kthe kgeneral ksentiment kabout kthe kspecific kbook. k The kproduct krating kcould kalso kbe kused
kto kunderstand khow kwell kthe kbook kis kliked kby kverified kbuyers. k Statistical kcorrelations kcould kbe krun
kamong kproduct kreview ksentiment, kproduct kratings kand kproduct ksales kto khelp kforecast kdemand kfor kthe
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
3
1
, Introduction kto kBusiness kAnalytics k1st kEdition kVernon kJ. kRichardson
kMarcia kWeidenmier kWatson
Chapter k1 kEnd-of-Chapter kAssignment kSolutions
Multiple kChoice kQuestions
1. (LO k1.1) kA kcoordinated, kstandardized kset kof kactivities kconducted kby kboth kpeople kand kequipment kto
kaccomplish ka kspecific kbusiness ktask kis kcalled k .
a. business kprocesses
b. business kanalysis
c. business kprocedure
d. business kvalue
2. (LO k1.2) kAccording kto kthe kinformation kvalue kchain, kdata kcombined kwith kcontext kis
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO k1.5) kWhich kphase kof kthe kSOAR kanalytics kmodel kaddresses kthe kproper kway kto kcommunicate
kresults kto kthe kdecision kmaker?
a. Specify kthe kquestion
b. Obtain kthe kdata
c. Analyze kthe kdata
d. Report kthe kresults
4. (LO k1.5) kWhich kphase kof kthe kSOAR kanalytics kmodel kinvolves kfinding kthe kmost kappropriate kdata kneeded
kto kaddress kthe kbusiness kquestion?
a. Specify kthe kquestion
b. Obtain kthe kdata
c. Analyze kthe kdata
d. Report kthe kresults
5. (LO k1.5) kWhich kquestions kseek kinformation kabout kTesla’s ksales kin kthe knext kquarter?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe
kforecast kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
2
, Chapter k01 k– kSpecify kthe kQuestion: kUsing kBusiness kAnalytics kto kAddress kBusiness kQuestions
6. (LO k1.5) kWhich kquestions kseek kinformation kon kthe krouting kof kproducts kfrom kQueretaro, kMexico kto
kChicago, kUnited kStates kin kthe klast kquarter?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
7. (LO k1.5) kWhich kquestions kask kwhy knet kincome kis kincreasing kwhen krevenues kare kdecreasing,
kcounter kto kexpectations?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
8. (LO k1.5) kWhich kquestions khelp kmanagers kunderstand khow kto korganize kfuture kshipments kbased kon
kexpected kdemand?
a. What khappened? kWhat kis khappening?
b. Why kdid kit khappen? kWhat kare kthe kcauses kof kpast kresults?
c. Will kit khappen kin kthe kfuture? kWhat kis kthe kprobability ksomething kwill khappen? kCan kwe kforecast
kwhat kwill khappen?
d. What kshould kwe kdo, kbased kon kwhat kwe kexpect kwill khappen? kHow kdo kwe koptimize kour
kperformance kbased kon kpotential kconstraints?
9. (LO k1.5) kWhich kterm krefers kto kthe kcombined kaccuracy, kvalidity, kand kconsistency kof kdata kstored kand
kused kover ktime?
a. Data kintegrity
b. Data koverload
c. Data kvalue
d. Information kvalue
10. (LO k1.3) kA kspecialist kwho kknows khow kto kwork kwith, kmanipulate, kand kstatistically ktest kdata kis ka
a. decision kmaker.
b. data kscientist.
c. data kanalyst.
d. decision kscientist.
11. (LO k1.4) kWhich ktype kof kanalysts kpredicts kthe kamount kof kmoney kthat ka kcompany kwill kreceive kfrom kits
kcustomers kto khelp kmanagement kevaluate kfuture kinvestments kbased kon kexpected kinvestment
kperformance, ksuch kas kinvestments kin kequipment kor kemployee ktraining?
a. Marketing kanalyst
b. Operations kanalyst
c. Financial kanalyst
d. Accounting kanalyst
12. (LO k1.4) kWhich ktype kof kanalyst kaddresses kquestions kregarding ktax kand kauditing?
a. Marketing kanalyst
b. Operations kanalyst
© kMcGraw kHill kLLC. kAll krights kreserved. kNo kreproduction kor kdistribution kwithout kthe kprior kwritten kconsent kof kMcGraw kHill
kLLC.
3
, c. Financial kanalyst
d. Accounting kanalyst
13. (LO k1.5) kSuppose ka kcompany khas ktimely kproduct kreviews kthat kare kavailable kwhen kneeded, kbut kthe
kreviews kare kbiased. kThese kproduct kreviews kare kwhich ktype kof kdata?
a. Reliable
b. Relevant
c. Curated
d. Consistent
14. (LO k1.6) kWhich kcommon kvisualization ktype kshows ktrends kin kvalues kover ktime?
a. Line kgraph
b. Scatterplot
c. Pie kchart
d. Bar kchart
15. (LO k1.6) kWhich kcommon kvisualization ktype kshows kthe kcomposition kof kvalues kover ktime?
a. Line kgraph
b. Scatterplot
c. Pie kchart
d. Bar kchart
Discussion kQuestions
1. (LO k1.1) kGive kfive kexamples kof kbusiness kprocesses kat kTesla. k How kdo kthey kcreate kbusiness kvalue kfor
kTesla kand kits kshareholders?
Suggested kSolution:
Answers kwill kvary,
1. Tesla kprocures kautomobile kparts kfrom kauto ksuppliers k– Because kof kTesla’s kunique kstyling, kgetting
kquality kparts kfrom kits ksuppliers kon ka ktimely kbasis kwill ksupport kits kmanufacturing kbusiness.
2. Tesla kmanufactures kbatteries kfor kits kelectric kvehicle kat kits kdesired kspecifications k– kThe kquantity
kand kquality kof kits kbatteries kare kof kcritical kimportance kto kTesla.
3. Accepting kand kprocessing kpreorders kfrom kits kcustomers k– kTesla kreceives ksome kindication kof kthe
kdemand kfor keach kof kits kproducts, kthat khelps kwith kplanning.
4. Tesla kmarkets kits kproducts k– kTesla kworks kto kget kTesla kproducts kin kthe kfront kof kmind kfor kits
kcustomers.
5. Tesla kcar kand ktruck kdesign k– kTesla kdesigns kits kautomobiles kin ka kway kthat kwill kappeal kto kits
kcustomers k(for kexample, kCybertruck).
2. (LO k1.2) kExplain kthe kinformation kvalue kchain kby ksummarizing khow kdata kare ktransformed kinto
kknowledge kinsights kfor kdecision-making. kUse kthe kexample kof ka kbook kreview kon kAmazon kand khow kit
kmight klead kAmazon kto kdecide khow kmany kof kthose kbooks kto kstock kat kits kwarehouses.
Suggested kSolution:
Amazon kallows kthose kwho kpurchase kbooks kand kother kproducts kat kits kwebsite kto kgive kproduct kreviews
kand kassign kproduct kratings. k The kproduct kreviews kmay kprovide ktext kwhich ktextual kanalytics kcould kuse
kto kunderstand kthe kgeneral ksentiment kabout kthe kspecific kbook. k The kproduct krating kcould kalso kbe kused
kto kunderstand khow kwell kthe kbook kis kliked kby kverified kbuyers. k Statistical kcorrelations kcould kbe krun
kamong kproduct kreview ksentiment, kproduct kratings kand kproduct ksales kto khelp kforecast kdemand kfor kthe
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
3
