Quantitative analysis for management 14th edition
by Barry Render and Michael Hanna
All Chapters 1-15 Covered
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,QUANTITATIVE ANALYSIS FOR MANAGEMENT, 14TH EDITION RENDER
C C C C C C
CHAPTER 1-15C
CHAPTER 1 C
Introduction to Quantitative Analysis
C C C
TEACHING SUGGESTIONS
C
TeachingCSuggestionC1.1:CImportanceCofCQualitativeCFactors.
SectionC1.1CgivesCstudentsCanCoverviewCofCquantitativeCanalysis.CInCthisCsection,CaCnumberCofCqu
alitativeCfactors,CincludingCfederalClegislationCandCnewCtechnology,CareCdiscussed.CStudentsCcanC
beCaskedCtoCdiscussCotherCqualitativeCfactorsCthatCcouldChaveCanCimpactConCquantitativeCanalysi
s.CWaitingClinesCandCprojectCplanningCcanCbeCusedCasCexamples.
TeachingCSuggestionC1.2:CDiscussingCOtherCQuantitativeCAnalysisCProblems.
SectionC1.2CcoversCanCapplicationCofCtheCquantitativeCanalysisCapproach.CStudentsCcanCbeCasked
CtoCdescribeCotherCproblemsCorCareasCthatCcouldCbenefitCfromCquantitativeCanalysis.
TeachingCSuggestionC1.3:CDiscussingCConflictingCViewpoints.
PossibleCproblemsCinCtheCQACapproachCareCpresentedCinCthisCchapter.CACdiscussionCofCconflictin
gCviewpointsCwithinCtheCorganizationCcanChelpCstudentsCunderstandCthisCproblem.CForCexample,C
howCmanyCpeopleCshouldCstaffCaCregistrationCdeskCatCaCuniversity?CStudentsCwillCwantCmoreCstaf
fCtoCreduceCwaitingCtime,CwhileCuniversityCadministratorsCwillCwantClessCstaffCtoCsaveCmoney.CACd
iscussionCofCtheseCtypesCofCconflictingCviewpointsCwillChelpCstudentsCunderstandCsomeCofCtheCpr
oblemsCofCusingCquantitativeCanalysis.
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,TeachingCSuggestionC1.4:CDifficultyCofCGettingCInputCData.
ACmajorCproblemCinCquantitativeCanalysisCisCgettingCproperCinputCdata.CStudentsCcanCbeCaskedCtoC
explainChowCtheyCwouldCgetCtheCinformationCtheyCneedCtoCdetermineCinventoryCorderingCorCcarryi
ngCcosts.CRole-
playingCwithCstudentsCassumingCtheCpartsCofCtheCanalystCwhoCneedsCinventoryCcostsCandCtheCinst
ructorCplayingCtheCpartCofCaCveteranCinventoryCmanagerCcanCbeCfunCandCinteresting.CStudentsCquic
klyClearnCthatCgettingCgoodCdataCcanCbeCtheCmostCdifficultCpartCofCusingCquantitativeCanalysis.
TeachingCSuggestionC1.5:CDealingCwithCResistanceCtoCChange.
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, ResistanceCtoCchangeCisCdiscussedCinCthisCchapter.CStudentsCcanCbeCaskedCtoCexplainChowCtheyC
wouldCintroduceCaCnewCsystemCorCchangeCwithinCtheCorganization.CPeopleCresistingCnewCapproac
hesCcanCbeCaCmajorCstumblingCblockCtoCtheCsuccessfulCimplementationCofCquantitativeCanalysis.C
StudentsCcanCbeCaskedCwhyCsomeCpeopleCmayCbeCafraidCofCaCnewCinventoryCcontrolCorCforecasti
ngCsystem.
SOLUTIONS TO DISCUSSION QUESTIONS AND PROBLEMS
C C C C C
1-
1.CQuantitativeCanalysisCinvolvesCtheCuseCofCmathematicalCequationsCorCrelationshipsCinCanalyzin
gCaCparticularCproblem.CInCmostCcases,CtheCresultsCofCquantitativeCanalysisCwillCbeConeCorCmoreCn
umbersCthatCcanCbeCusedCbyCmanagersCandCdecisionCmakersCinCmakingCbetterCdecisions.CCalcul
atingCratesCofCreturn,CfinancialCratiosCfromCaCbalanceCsheetCandCprofitCandClossCstatement,Cdeter
miningCtheCnumberCofCunitsCthatCmustCbeCproducedCinCorderCtoCbreakCeven,CandCmanyCsimilarCtec
hniquesCareCexamplesCofCquantitativeCanalysis.CQualitativeCanalysisCinvolvesCtheCinvestigationCofC
factorsCinCaCdecision-
makingCproblemCthatCcannotCbeCquantifiedCorCstatedCinCmathematicalCterms.CTheCstateCofCtheCec
onomy,CcurrentCorCpendingClegislation,CperceptionsCaboutCaCpotentialCclient,CandCsimilarCsituatio
nsCrevealCtheCuseCofCqualitativeCanalysis.CInCmostCdecision-
makingCproblems,CbothCquantitativeCandCqualitativeCanalysisCareCused.CInCthisCbook,Chowever,Cw
eCemphasizeCtheCtechniquesCandCapproachesCofCquantitativeCanalysis.
1-
2.CQuantitativeCanalysisCisCtheCscientificCapproachCtoCmanagerialCdecisionCmaking.CThisCtypeCofCa
nalysisCisCaClogicalCandCrationalCapproachCtoCmakingCdecisions.CEmotions,Cguesswork,CandCwhim
CareCnotCpartCofCtheCquantitativeCanalysisCapproach.CACnumberCofCorganizationsCsupportCtheCuseC
ofCtheCscientificCapproach:CtheCInstituteCforCOperationCResearchCandCManagementCScienceC(INF
ORMS),CDecisionCSciencesCInstitute,CandCAcademyCofCManagement.
1-
3.CTheCthreeCcategoriesCofCbusinessCanalyticsCareCdescriptive,Cpredictive,CandCprescriptive.CDesc
riptiveCanalyticsCprovidesCanCindicationCofChowCthingsCwereCperformedCinCtheCpast.CPredictiveCan
alyticsCusesCpastCdataCtoCforecastCwhatCwillChappenCinCtheCfuture.CPrescriptiveCanalyticsCusesCop
timizationCandCotherCmodelsCtoCpresentCbetterCwaysCforCaCcompanyCtoCoperateCtoCreachCgoalsCan
dCobjectives.
1-4.CQuantitativeCanalysisCisCaCstep-by-
stepCprocessCthatCallowsCdecisionCmakersCtoCinvestigateCproblemsCusingCquantitativeCtechnique
s.CTheCstepsCofCtheCquantitativeCanalysisCprocessCincludeCdefiningCtheCproblem,CdevelopingCaCmo
del,CacquiringCinputCdata,CdevelopingCaCsolution,CtestingC theCsolution,CanalyzingCtheCresults,CandCi
mplementingCtheCresults.CInCeveryCcase,CtheCanalysisCbeginsCwithCdefiningCtheCproblem.CTheCprob
lemCcouldCbeCtooCmanyCstockouts,CtooCmanyCbadC debts,CorCdeterminingCtheCproductsCtoCproduc
eCthatCwillCresultCinCtheCmaximumCprofitCforCtheCorganization.CAfterCtheCproblemsChaveCbeenCdefi
ned,CtheCnextCstepCisCtoCdevelopConeCorCmoreCmodels.CTheseCmodelsCcouldCbeCinventoryCcontrolC
models,CmodelsCthatCdescribeCtheCdebtCsituationCinCtheCorganization,CandCsoCon.COnceCtheCmode
lsChaveCbeenCdeveloped,CtheCnextCstepCisCtoCacquireCinputCdata.CInCtheCinventoryCproblem,CforCex
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