Introduction to Business Analytics 1st Edition Solution Manual | Richardson & Watson – 2025 Step-by-Step Analytics Solutions

Chapterg01g–
gSpecifygthegQuestion:gUsinggBusinessgAnalyticsgtogAddressgBusinessgQuestions



Chapter 1 End-of-Chapter Assignment Solutions
g g g g




MultiplegChoicegQuestions
1. (LOg1.1)gAgcoordinated,gstandardizedgsetgofgactivitiesgconductedgbygbothgpeoplegandgequipmentgtogaccomplis
hgagspecificgbusinessgtaskgisgcalledg .
a. businessgprocesses
b. businessganalysis
c. businessgprocedure
d. businessgvalue

2. (LOg1.2)gAccordinggtogtheginformationgvaluegchain,gdatagcombinedgwithgcontextgis
a. Information.
b. Knowledge.
c. Insight.
d. Value.

3. (LOg 1.5)gWhichgphasegofgthegSOARganalyticsgmodelgaddressesgthegpropergwaygtogcommunicategresultsgtog
thegdecisiongmaker?
a. Specifygthegquestion
b. Obtaingthegdata
c. Analyzegthegdata
d. Reportgthegresults

4. (LOg1.5)gWhichgphasegofgthegSOARganalyticsgmodelginvolvesgfindinggthegmostgappropriategdatagneededgtogaddr
essgthegbusinessgquestion?
a. Specifygthegquestion
b. Obtaingthegdata
c. Analyzegthegdata
d. Reportgthegresults

5. (LOg1.5)gWhichgquestionsgseekginformationgaboutgTesla’sgsalesgingthegnextgquarter?
a. Whatghappened?gWhatgisghappening?
b. Whygdidgitghappen?gWhatgaregthegcausesgofgpastgresults?
c. Willgitghappengingthegfuture?gWhatgisgthegprobabilitygsomethinggwillghappen?gCangwegforecastgw
hatgwillghappen?
d. Whatgshouldgwegdo,gbasedgongwhatgwegexpectgwillghappen?gHowgdogwegoptimizegourgperformancegbas
edgongpotentialgconstraints?


6. (LOg1.5)gWhichgquestionsgseekginformationgongthegroutinggofgproductsgfromgQueretaro,gMexicogtogChica
go,gUnitedgStatesgingtheglastgquarter?
a. Whatghappened?gWhatgisghappening?
b. Whygdidgitghappen?gWhatgaregthegcausesgofgpastgresults?
c. Willgitghappengingthegfuture?gWhatgisgthegprobabilitygsomethinggwillghappen?gCangwegforecastgwhatg
willghappen?
d. Whatgshouldgwegdo,gbasedgongwhatgwegexpectgwillghappen?gHowgdogwegoptimizegourgperformancegbas
edgongpotentialgconstraints?


©gMcGrawgHillgLLC.gAllgrightsgreserved.gNogreproductiongorgdistributiongwithoutgthegpriorgwrittengconsentgofgMcGrawgHillgLLC.

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, Chapterg01g–
gSpecifygthegQuestion:gUsinggBusinessgAnalyticsgtogAddressgBusinessgQuestions
7. (LOg1.5)gWhichgquestionsgaskgwhygnetgincomegisgincreasinggwhengrevenuesgaregdecreasing,gcounter
gtogexpectations?
a. Whatghappened?gWhatgisghappening?
b. Whygdidgitghappen?gWhatgaregthegcausesgofgpastgresults?
c. Willgitghappengingthegfuture?gWhatgisgthegprobabilitygsomethinggwillghappen?gCangwegforecastgwhatg
willghappen?
d. Whatgshouldgwegdo,gbasedgongwhatgwegexpectgwillghappen?gHowgdogwegoptimizegourgperformancegbas
edgongpotentialgconstraints?

8. (LOg1.5)gWhichgquestionsghelpgmanagersgunderstandghowgtogorganizegfuturegshipmentsgbasedgongexpect
edgdemand?
a. Whatghappened?gWhatgisghappening?
b. Whygdidgitghappen?gWhatgaregthegcausesgofgpastgresults?
c. Willgitghappengingthegfuture?gWhatgisgthegprobabilitygsomethinggwillghappen?gCangwegforecastgwhatg
willghappen?
d. Whatgshouldgwegdo,gbasedgongwhatgwegexpectgwillghappen?gHowgdogwegoptimizegourgperforma
ncegbasedgongpotentialgconstraints?

9. (LOg 1.5)gWhichgtermgrefersgtogthegcombinedgaccuracy,gvalidity,gandgconsistencygofgdatagstoredgandgusedgo
vergtime?
a. Datagintegrity
b. Datagoverload
c. Datagvalue
d. Informationgvalue

10. (LOg1.3)gAgspecialistgwhogknowsghowgtogworkgwith,gmanipulate,gandgstatisticallygtestgdatagisga
a. decisiongmaker.
b. datagscientist.
c. dataganalyst.
d. decisiongscientist.

11. (LOg 1.4)gWhichgtypegofganalystsgpredictsgthegamountgofgmoneygthatgagcompanygwillgreceivegfromgitsgcustomer
sgtoghelpgmanagementgevaluategfutureginvestmentsgbasedgongexpectedginvestmentgperformance,gsuchgasginve
stmentsgingequipmentgorgemployeegtraining?
a. Marketingganalyst
b. Operationsganalyst
c. Financialganalyst
d. Accountingganalyst

12. (LOg1.4)gWhichgtypegofganalystgaddressesgquestionsgregardinggtaxgandgauditing?
a. Marketingganalyst
b. Operationsganalyst
c. Financialganalyst
d. Accountingganalyst

13. (LOg 1.5)gSupposegagcompanyghasgtimelygproductgreviewsgthatgaregavailablegwhengneeded,gbutgthegreviewsg
aregbiased.gThesegproductgreviewsgaregwhichgtypegofgdata?
a. Reliable
b. Relevant
c. Curated
d. Consistent
©gMcGrawgHillgLLC.gAllgrightsgreserved.gNogreproductiongorgdistributiongwithoutgthegpriorgwrittengconsentgofgMcGrawgHillgLLC.



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, Chapterg01g–
gSpecifygthegQuestion:gUsinggBusinessgAnalyticsgtogAddressgBusinessgQuestions
14. (LOg1.6)gWhichgcommongvisualizationgtypegshowsgtrendsgingvaluesgovergtime?
a. Lineggraph
b. Scatterplot
c. Piegchart
d. Bargchart

15. (LOg1.6)gWhichgcommongvisualizationgtypegshowsgthegcompositiongofgvaluesgovergtime?
a. Lineggraph
b. Scatterplot
c. Piegchart
d. Bargchart


DiscussiongQuestions
1. (LOg 1.1)gGivegfivegexamplesgofgbusinessgprocessesgatgTesla.g HowgdogtheygcreategbusinessgvaluegforgTeslagand
gitsgshareholders?



SuggestedgSolution:
Answersgwillgvary,
1. Teslagprocuresgautomobilegpartsgfromgautogsuppliersg–
BecausegofgTesla’sguniquegstyling,ggettinggqualit
ygpartsgfromgitsgsuppliersgongagtimelygbasisgwillgsupportgitsgmanufacturinggbusiness.
2. Teslagmanufacturesgbatteriesgforgitsgelectricgvehiclegatgitsgdesiredgspecificationsg–
gThegquantitygandgqualitygofgitsgbatteriesgaregofgcriticalgimportancegtogTesla.

3. Acceptinggandgprocessinggpreordersgfromgitsgcustomersg–
gTeslagreceivesgsomegindicationgofgthegdemandgforgeachgofgitsgproducts,gthatghelpsgwithgplanning.

4. Teslagmarketsgitsgproductsg–gTeslagworksgtoggetgTeslagproductsgingthegfrontgofgmindgforgitsgcustomers.
5. Teslagcargandgtruckgdesigng–
gTeslagdesignsgitsgautomobilesgingagwaygthatgwillgappealgtogitsgcustomersg(forgexample,gCybertruck).



2. (LOg 1.2)gExplaingtheginformationgvaluegchaingbygsummarizingghowgdatagaregtransformedgintogknowledgeginsigh
tsgforgdecision-
making.gUsegthegexamplegofgagbookgreviewgongAmazongandghowgitgmightgleadgAmazongtogdecideghowgmanygof
gthosegbooksgtogstockgatgitsgwarehouses.



SuggestedgSolution:
Amazongallowsgthosegwhogpurchasegbooksgandgothergproductsgatgitsgwebsitegtoggivegproductgreviewsgandgassig
ngproductgratings.g Thegproductgreviewsgmaygprovidegtextgwhichgtextualganalyticsgcouldgusegtogunderstandgtheg
generalgsentimentgaboutgthegspecificgbook.g Thegproductgratinggcouldgalsogbegusedgtogunderstandghowgwellgthe
gbookgisglikedgbygverifiedgbuyers.g Statisticalgcorrelationsgcouldgbegrungamonggproductgreviewgsentiment,gprodu
ctgratingsgandgproductgsalesgtoghelpgforecastgdemandgforgthegproduct.g ThisgwillghelpgAmazongdetermineghowg
manygbooksgtogkeepgingitsgwarehousegreadygforgdelivery.
Thisgisgangexamplegofghowgdatagturnsgintoginformation,gknowledgegandgultimatelyghelpsgwithgdecisiongmaking.


3. (LOg 1.3)gExplaingtheginformationgvaluegchaingbygsummarizingghowgdatagaregtransformedgintogknowledgeginsig
htsgforgdecision-
making.gUsegthegexamplegofgagbookgreviewgofgthisgbookgongAmazongandghowgitgmightghelpgthegpublisher,gMc
GrawgHill,gdeterminegwhethergtogrevisegthisgbookgforgagnew,gupdatedgeditiongasgthegdisciplinegofgdataganalyti
csgevolves.
3

, Chapterg01g–
gSpecifygthegQuestion:gUsinggBusinessgAnalyticsgtogAddressgBusinessgQuestions


©gMcGrawgHillgLLC.gAllgrightsgreserved.gNogreproductiongorgdistributiongwithoutgthegpriorgwrittengconsentgofgMcGrawgHillgLLC.




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