Solution manual for introduction to business analytics 1st edition by Richardson & Watson all 12 chapters complete

Chaptern01n–
nSpecifynthenQuestion:nUsingnBusinessnAnalyticsntonAddressnBusinessnQuestions



Solution Manual for Introduction to Business Analytics,
n n n n n n n




1st Edition
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By Vernon Richardson and Marcia Watson
n n n n n




Verified Chapter's 1 - 12 | Complete
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, Chaptern01n–
nSpecifynthenQuestion:nUsingnBusinessnAnalyticsntonAddressnBusinessnQuestions




TABLE OF CONTENTS n n n




Chaptern1:nSpecifynthenQuestion:nUsingnBusinessnAnalyticsntonAddressnBusinessnQuestionsnn

Chaptern2:nObtainnthenData:nAnnIntroductionntonBusinessnDatanSourcesnn

Chaptern3:nAnalyzenthenData:nBasicnStatisticsnandnToolsnRequiredninnBusinessnAnalyticsnn

Chaptern4:nAnalyzenthenData:nExploratorynBusinessnAnalyticsn(DescriptivenAnalyticsnandnDiagnosticnAnalytics)nn

Chaptern5:nAnalyzenthenData:nConfirmatorynBusinessnAnalyticsn(PredictivenAnalyticsnandnPrescriptivenAnalytics)nn

Chaptern6:nReportnthenResults:nUsingnDatanVisualizationnn

Chaptern7:nMarketingnAnalyticsnn

Chaptern8:nAccountingnAnalyticsnn

Chaptern9:nFinancialnAnalyticsnn

Chaptern10:nOperationsnAnalyticsnn

Chaptern11:nAdvancednBusinessnAnalyticsnn

Chaptern12:nUsingnthenSOARnAnalyticsnModelntonPutnItnAllnTogether:nThreenCapstonenProjectsnn

, Chaptern01n–
nSpecifynthenQuestion:nUsingnBusinessnAnalyticsntonAddressnBusinessnQuestions




Chapter 1 End-of-Chapter Assignment Solutions
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MultiplenChoicenQuestions
1. n(LOn1.1)nAncoordinated,nstandardizednsetnofnactivitiesnconductednbynbothnpeoplenandnequipmentntonaccomplishn
anspecificnbusinessntasknisncalled .
a. businessnprocesses
b. businessnanalysis
c. businessnprocedure
d. businessnvalue

2. (LOn1.2)nAccordingntontheninformationnvaluenchain,ndatancombinednwithncontextnis
a. Information.
b. Knowledge.
c. Insight.
d. Value.

3. (LOn1.5)nWhichnphasenofnthenSOARnanalyticsnmodelnaddressesnthenpropernwayntoncommunicatenresultsntonth
endecisionnmaker?
a. Specifynthenquestion
b. Obtainnthendata
c. Analyzenthendata
d. Reportnthenresults

4. (LOn1.5)nWhichnphasenofnthenSOARnanalyticsnmodelninvolvesnfindingnthenmostnappropriatendatanneededntonaddres
snthenbusinessnquestion?
a. Specifynthenquestion
b. Obtainnthendata
c. Analyzenthendata
d. Reportnthenresults

5. (LOn1.5)nWhichnquestionsnseekninformationnaboutnTesla’snsalesninnthennextnquarter?
a. Whatnhappened?nWhatnisnhappening?
b. Whyndidnitnhappen?nWhatnarenthencausesnofnpastnresults?
c. Willnitnhappenninnthenfuture?nWhatnisnthenprobabilitynsomethingnwillnhappen?nCannwenforecastnwha
tnwillnhappen?
d. Whatnshouldnwendo,nbasednonnwhatnwenexpectnwillnhappen?nHowndonwenoptimizenournperformancenbase
dnonnpotentialnconstraints?


6. (LOn1.5)nWhichnquestionsnseekninformationnonnthenroutingnofnproductsnfromnQueretaro,nMexicontonChicago
,nUnitednStatesninnthenlastnquarter?
a. Whatnhappened?nWhatnisnhappening?
b. Whyndidnitnhappen?nWhatnarenthencausesnofnpastnresults?
c. Willnitnhappenninnthenfuture?nWhatnisnthenprobabilitynsomethingnwillnhappen?nCannwenforecastnwhatnwil
lnhappen?
d. Whatnshouldnwendo,nbasednonnwhatnwenexpectnwillnhappen?nHowndonwenoptimizenournperformancenbase
dnonnpotentialnconstraints?

, Chaptern01n–
nSpecifynthenQuestion:nUsingnBusinessnAnalyticsntonAddressnBusinessnQuestions
7. (LOn1.5)nWhichnquestionsnasknwhynnetnincomenisnincreasingnwhennrevenuesnarendecreasing,ncounternt
onexpectations?
a. Whatnhappened?nWhatnisnhappening?
b. Whyndidnitnhappen?nWhatnarenthencausesnofnpastnresults?
c. Willnitnhappenninnthenfuture?nWhatnisnthenprobabilitynsomethingnwillnhappen?nCannwenforecastnwhatnwil
lnhappen?
d. Whatnshouldnwendo,nbasednonnwhatnwenexpectnwillnhappen?nHowndonwenoptimizenournperformancenbase
dnonnpotentialnconstraints?

8. (LOn1.5)nWhichnquestionsnhelpnmanagersnunderstandnhowntonorganizenfuturenshipmentsnbasednonnexpecte
dndemand?
a. Whatnhappened?nWhatnisnhappening?
b. Whyndidnitnhappen?nWhatnarenthencausesnofnpastnresults?
c. Willnitnhappenninnthenfuture?nWhatnisnthenprobabilitynsomethingnwillnhappen?nCannwenforecastnwhatnwil
lnhappen?
d. Whatnshouldnwendo,nbasednonnwhatnwenexpectnwillnhappen?nHowndonwenoptimizenournperformanc
enbasednonnpotentialnconstraints?

9. (LOn1.5)nWhichntermnrefersntonthencombinednaccuracy,nvalidity,nandnconsistencynofndatanstorednandnusednove
rntime?
a. Datanintegrity
b. Datanoverload
c. Datanvalue
d. Informationnvalue

10. (LOn1.3)nAnspecialistnwhonknowsnhowntonworknwith,nmanipulate,nandnstatisticallyntestndatanisna
a. decisionnmaker.
b. datanscientist.
c. datananalyst.
d. decisionnscientist.

11. (LOn1.4)nWhichntypenofnanalystsnpredictsnthenamountnofnmoneynthatnancompanynwillnreceivenfromnitsncustomersnt
onhelpnmanagementnevaluatenfutureninvestmentsnbasednonnexpectedninvestmentnperformance,nsuchnasninvestme
ntsninnequipmentnornemployeentraining?
a. Marketingnanalyst
b. Operationsnanalyst
c. Financialnanalyst
d. Accountingnanalyst

12. (LOn1.4)nWhichntypenofnanalystnaddressesnquestionsnregardingntaxnandnauditing?
a. Marketingnanalyst
b. Operationsnanalyst
c. Financialnanalyst
d. Accountingnanalyst

13. (LOn1.5)nSupposenancompanynhasntimelynproductnreviewsnthatnarenavailablenwhennneeded,nbutnthenreviewsnar
enbiased.nThesenproductnreviewsnarenwhichntypenofndata?
a. Reliable
b. Relevant
c. Curated
d. Consistent
©nMcGrawnHillnLLC.nAllnrightsnreserved.nNonreproductionnorndistributionnwithoutnthenpriornwrittennconsentnofnMcGrawnHillnLLC.



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