版權(quán)說(shuō)明:本文檔由用戶(hù)提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請(qǐng)進(jìn)行舉報(bào)或認(rèn)領(lǐng)
文檔簡(jiǎn)介
Copyright2019?McGraw-HillEducation.Allrightsreserved.NoreproductionordistributionwithoutthepriorwrittenconsentofMcGraw-HillEducation.
DataAnalyticsforAccounting,1e(Richardson)
Chapter3ModelingandEvaluation:GoingfromDefiningBusinessProblemsandDataUnderstandingtoAnalyzingDataandAnsweringQuestions
1)Benford'sLawisanabsoluteandalldatamustconform.
Answer:FALSE
Difficulty:1Easy
Topic:ExampleofProfilinginAuditingandContinuousAuditing
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
2)Adecisiontreecanbeusedtodividedataintosmallergroups.
Answer:TRUE
Difficulty:1Easy
Topic:ClassificationTerminology
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology
3)Datareductionisadataapproachusedtoreducetheamountofinformationthatneedstobeconsideredtofocusonthemostcriticalitems.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology
4)Regressionisadataapproachusedtoestimateorpredict,foreachunit,thenumericalvalueofsomevariableusingsometypeofstatisticalmodel.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology
5)Linkpredictionisadataapproachusedtoestimateorpredict,foreachunit,thenumericalvalueofsomevariableusingsometypeofstatisticalmodel.
Answer:FALSE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
6)Existingdatathathasbeenmanuallyevaluatedandassignedaclassisoftenreferredtoastestdata.
Answer:FALSE
Difficulty:2Medium
Topic:ClassificationTerminology
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
7)Co-occurrencegroupingcouldbeusedtomatchvendorsbygeographicregion.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
8)Fuzzymatchingisadataapproachusedtoidentifysimilarindividualsbasedondataknownaboutthem.
Answer:FALSE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
9)Alibabaanditsattempttoidentifysellerandcustomerfraudbasedonvariouscharacteristicsknownaboutthemisanexampleofsimilaritymatching.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
10)Fuzzymatchingisacomputer-assistedtechniqueoffindingmatchesthatarelessthan100percentperfectbyfindingcorrespondencesbetweenportionsofthetextofeachpotentialmatch.
Answer:TRUE
Difficulty:1Easy
Topic:ExampleofDataReductioninInternalandExternalAuditing
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
11)ThePinIMPACTCyclerepresentsperformingtestplan.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
12)Clusteringisadataapproachusedtodivideindividualsintogroupsinausefulormeaningfulway.
Answer:TRUE
Difficulty:1Easy
Topic:ClusteringDataApproach
LearningObjective:03-05UnderstandtheclusteringapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
13)Anexampleofclassificationwouldbeacreditcardcompanyflaggingatransactionasbeingapprovedorpotentiallybeingfraudulentanddenyingpayment.
Answer:TRUE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
14)Thedataapproachusedtocharacterizethetypicalbehaviorofanindividual,grouporpopulationbygeneratingsummarystatisticsaboutthedataisreferredtoasclassification.
Answer:FALSE
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
15)XBRLisaglobalstandardforexchangingfinancialreportinginformationthatusesXML.
Answer:TRUE
Difficulty:1Easy
Topic:ExamplesofDataReductioninOtherAccountingAreas
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
16)XBRLisusedtofacilitatetheexchangeoffinancialreportinginformationbetweenthecompanyandtheSecuritiesandExchangeCommission.
Answer:TRUE
Difficulty:1Easy
Topic:ExamplesofDataReductioninOtherAccountingAreas
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
17)Dataprofilingtypicallyinvolvesunstructureddata.
Answer:FALSE
Difficulty:1Easy
Topic:ProfilingDataApproach
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
18)Atargetisamanuallyassignedcategoryappliedtoarecordbasedonanevent.
Answer:FALSE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
19)Whenconsideringaquestionsuchas"Doourcustomersformnaturalgroupsbasedonsimilarattributes?"youwoulduseanunsupervisedapproach.
Answer:TRUE
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
20)Co-occurrencegroupingisanexampleofasupervisedapproach.
Answer:FALSE
Difficulty:1Easy
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;BBIndustry
21)Allofthefollowingareexamplesofasupervisedapproachtoevaluationdataexcept:
A)Causalmodeling
B)Datareduction
C)Linkprediction
D)Regression
Answer:B
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
22)Allofthefollowingareexamplesofanunsupervisedapproachtoevaluationdataexcept:
A)Similaritymatching
B)Clustering
C)Profiling
D)Co-occurrencegrouping
Answer:A
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
23)Whichofthefollowingbestdescribesanunsupervisedapproachtotheevaluationofdata?
A)Dataexplorationthatisfreefromoversightbyasuperior
B)Dataexplorationthatexaminestherelationshipsbetweenvariablesthatarehypothesizedtoexist
C)Dataexplorationthatlooksforpotentialpatternsofinterest
D)Dataexplorationthatisconductedwithdirectoversightbyasuperior
Answer:C
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
24)Whichofthefollowingbestdescribesasupervisedapproachtotheevaluationofdata?
A)Dataexplorationthatisfreefromoversightbyasuperior
B)Dataexplorationthatisconductedwithdirectoversightbyasuperior
C)Dataexplorationthatexaminestherelationshipsbetweenvariablesthatarehypothesizedtoexist
D)Dataexplorationthatlooksforpotentialpatternsofinterest
Answer:C
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
25)Whichapproachtodataanalyticsattemptstoassigneachunitinapopulationintoasmallsetofcategories?
A)Classification
B)Regression
C)Similaritymatching
D)Co-occurrencegrouping
Answer:A
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
26)Whichapproachtodataanalyticsattemptstodivideindividualsintogroupsinausefulormeaningfulway?
A)Clustering
B)Datareduction
C)Similaritymatching
D)Co-occurrencegrouping
Answer:A
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
27)Whichapproachtodataanalyticsattemptstoidentifysimilarindividualsbasedondataknownaboutthem?
A)Classification
B)Clustering
C)Similaritymatching
D)Co-occurrencegrouping
Answer:C
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
28)Whichapproachtodataanalyticsattemptstodiscoverassociationsbetweenindividualsbasedontransactionsinvolvingthem?
A)Classification
B)Regression
C)Similaritymatching
D)Co-occurrencegrouping
Answer:D
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
29)Whichapproachtodataanalyticsattemptstoforecastarelationshipbetweentwodataitems?
A)Linkprediction
B)Regression
C)Similaritymatching
D)Co-occurrencegrouping
Answer:A
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
30)Whichapproachtodataanalyticsattemptstopredict,foreachunit,thenumericalvalueofsomevariable?
A)Classification
B)Regression
C)Similaritymatching
D)Linkprediction
Answer:B
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
31)Whichapproachtodataanalyticsattemptstocharacterizethetypicalbehaviorofanindividual,grouporpopulationbygeneratingsummarystatisticsaboutthedata?
A)Classification
B)Regression
C)Profiling
D)Linkprediction
Answer:C
Difficulty:2Medium
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
32)________referstodatathatisstoredinadatabaseorspreadsheetthatisreadilysearchable.
A)Trainingdata
B)Unstructureddata
C)Structureddata
D)Testdata
Answer:C
Difficulty:2Medium
Topic:ProfilingDataApproach
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
33)Usingsocialmediatolookforrelationshipsbetweenrelatedpartiesthatarenototherwisedisclosedtoidentifyrelatedpartytransactionsisanexampleof________.
A)Classification
B)Regression
C)Profiling
D)Linkprediction
Answer:D
Difficulty:3Hard
Topic:PerformingtheTestPlan:DefiningDataAnalyticsApproaches
LearningObjective:03-01DefineDataAnalyticsApproaches.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
34)Dataprofilingisusedtoassessdataqualityandinternalcontrols.Ittypicallyinvolvesthefollowingstepsexcept:
A)Filtertheresults.
B)Identifytheobjectsoractivityyouwanttoprofile.
C)Determinethetypesofprofilingyouwanttoperform.
D)Setboundariesorthresholdsfortheactivity.
Answer:A
Difficulty:2Medium
Topic:ProfilingDataApproach
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
35)Regressionanalysistypicallyinvolvesthefollowingstepsexcept:
A)Identifythevariablesthatmightpredictanoutcome.
B)Identifytheparametersofthemodel.
C)Setboundariesorthresholds.
D)Determinethefunctionalformoftherelationship.
Answer:C
Difficulty:2Medium
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
36)Datareductiontypicallyinvolvesthefollowingstepsexcept:
A)Identifytheattributeyouwouldliketoreduceorfocuson.
B)Identifytheparametersofthemodel.
C)Filtertheresults.
D)Interprettheresults.
Answer:B
Difficulty:2Medium
Topic:DataReductionDataApproach
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
37)Whenworkingwithapredictivemodel,underfittingthedataismostlikelycausedby________.
A)anoverlycomplexmodel
B)anoverlysimplemodel
C)overpruningthedata
D)alackofdatareduction
Answer:B
Difficulty:2Medium
Topic:EvaluatingClassifiers
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
38)Ingeneral,themorecomplexthemodel,thegreaterthechanceof________.
A)Overfittingthedata
B)Underfittingthedata
C)Pruningthedata
D)Theneedtoreducetheamountofdataconsidered
Answer:A
Difficulty:2Medium
Topic:EvaluatingClassifiers
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
39)Whileoverfittingdatacouldleadtoanerrorrateof0(zero),itisunlikelythatyouwouldbeableto________yourresults.
A)define
B)specify
C)articulate
D)generalize
Answer:D
Difficulty:3Hard
Topic:EvaluatingClassifiers
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
40)Whichofthefollowingbestdescribesanindependentvariable?
A)Output
B)Input
C)Application
D)Operation
Answer:B
Difficulty:1Easy
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
41)Whichofthefollowingbestdescribesadependentvariable?
A)Output
B)Input
C)Application
D)Operation
Answer:A
Difficulty:1Easy
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
42)Understandingandpredictinginventoryobsolescenceisanimportantdeterminationforretailcompanies.Whenusingcompetitorsellingpricestoestimatetheinventoryobsolescencereserve,theinventoryobsolescencereserverepresentswhichofthefollowing?
A)Independentvariable
B)Dependentvariable
C)Function
D)StatisticalModel
Answer:B
Difficulty:3Hard
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
43)Understandingandpredictingwarrantyexpenseisanimportantdeterminationformanufacturingfirms.Whenusinghistoricalclaimsdatatoestimatethecurrentperiod'swarrantyexpense,thehistoricalclaimsdatarepresentswhichofthefollowing?
A)Independentvariable
B)Dependentvariable
C)Function
D)StatisticalModel
Answer:A
Difficulty:3Hard
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
44)Oneofthekeytasksofbankauditorsistoconsidertheamountoftheloanlossreserve.Whendevelopingamodeltoestimatethecurrentyear'sloanlossreserveamount,whichofthefollowingwouldbeleastlikelytobeincludedasanindependentvariable?
A)Originalloanapprovalamount
B)Customerloanhistory
C)Currentagedloans
D)Collectionssuccess
Answer:A
Difficulty:3Hard
Topic:RegressionDataApproach
LearningObjective:03-04UnderstandtheregressionandclassificationapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
45)Theshortsurveysregardingdiningpreferencesrequestedatthebottomoftherestaurantbillareanexampleofwhichdataapproach?
A)Clustering
B)Regression
C)Similaritymatching
D)Linkprediction
Answer:A
Difficulty:2Medium
Topic:ClusteringDataApproach
LearningObjective:03-05UnderstandtheclusteringapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
46)Retailstoresoftenrequestcustomers'zipcodesattheendofasalestransaction.Thisisanexampleofwhichdataapproach?
A)Clustering
B)Regression
C)Similaritymatching
D)Classification
Answer:A
Difficulty:2Medium
Topic:ClusteringDataApproach
LearningObjective:03-05UnderstandtheclusteringapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
47)
________isexistingdatathathasbeenmanuallyevaluatedandassignedaclassand
________isexistingdatausedtoevaluatethemodel.
A)Testdata;Trainingdata
B)Trainingdata;Testdata
C)Structureddata;Unstructureddata
D)Unstructureddata;Structureddata
Answer:B
Difficulty:1Easy
Topic:ClassificationTerminology
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
48)
________markthesplitbetweenoneclassandanother.
A)Decisiontrees
B)Identifyingquestions
C)Decisionboundaries
D)Linearclassifiers
Answer:C
Difficulty:1Easy
Topic:ClassificationTerminology
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
49)________statesthatinmanynaturallyoccurringcollectionsofnumbers,theleadingsignificantdigitislikelytobesmall.
A)Leadingdigitshypothesis
B)Moore'slaw
C)Benford'slaw
D)Classification
Answer:C
Difficulty:2Medium
Topic:ExampleofProfilinginAuditingandContinuousAuditing
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Remember
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
50)Unawareofdataanalysistoolsavailabletotheinternalauditors,astoreemployeefrequentlyprocessescashreturnswithoutareceiptfor$99,whichisjustbelowtheamountrequiringmanagerapprovalof$100.Ananalysisusingwhichofthefollowingwouldlikely(andquickly)identifytheemployee'sfraudulentbehavior?
A)Leadingdigitshypothesis
B)Moore'slaw
C)Benford'slaw
D)Clustering
Answer:C
Difficulty:3Hard
Topic:ExampleofProfilinginAuditingandContinuousAuditing
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
51)Whatisthedifferencebetweenstructureddataandunstructureddata?Provideanexampleofeach.
Answer:Answersmayvaryslightly!
? Structureddataaredatathatareorganizedandresideinafixedfieldwitharecordorafile.Examplesinclude:Relationaldatabase,spreadsheet,orotherformatsthatarereadilysearchablebysearchalgorithms.
? Unstructureddataaredatathateitherdoesnothaveapre-defineddatamodelorisnotorganizedinapre-definedmanner.Examplesinclude:Photographs,Instagram,Twitter,orsatelliteImages.
Difficulty:2Medium
Topic:ProfilingDataApproach;DataReductionDataApproach
LearningObjective:03-02ExplaintheprofilingapproachtoDataAnalytics;03-03DescribethedatareductionapproachtoDataAnalytics
Bloom's:Understand
AACSB:ReflectiveThinking
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;BBIndustry
52)Decisiontreesareusedtodividedataintosmallergroupsbysplittingthedataateachbranchintotwoormoregroups.However,thismethodcouldleadtounintendedconsequencesifthedecisiontreeisnotpruned.Describethepruningprocess,whenitcanoccurandthebenefitsofusingit.
Answer:Answerswillvarybutshouldincludesomeoftheseitems.
? Pruningremovesbranchesfromadecisiontreetoavoidoverfittingthemodel.
o Pre-pruningoccursduringthemodelgeneration.Themodelstopscreatingnewbrancheswhentheinformationusefulnessofanadditionalbranchislow.
o Post-pruningevaluatesthecompletemodelanddiscardsbranchesafterthefact.
Difficulty:3Hard
Topic:ClassificationTerminology
LearningObjective:03-03DescribethedatareductionapproachtoDataAnalytics.
Bloom's:Apply
AACSB:ReflectiveThinking;KnowledgeApplication
AICPA:BBLeveragingTechnology;FNLeveragingTechnology;FNDecisionMaking
53)Chapter3discussed5(five)dataanalyticsapproachesortechniquesaremostcommontoaddressouraccountingquestions.Listanddefine3ofthe5dataanalyticsapproaches.Next,describehoweachofthe3dataanalyticsapproachesyoulistcouldbeusedbycreditcardcompaniestoidentifyfraudulentcreditcardactivity.
Answer:
? Classification:Adataapproachusedtoassigneachunitinapopulationintoafewcategoriespotentiallytohelpwithpredictions.
o Creditcardcompaniesestablishmodelstopredictfraudanddecidewhethertoacceptorrejectaproposedcreditcardtransaction.Apotentialmodelmaybethefollowing:
Transactionapproval=f(locationofcurrenttransaction,locationoflasttransaction,amountofcurrenttransaction,priorhistoryoftravelofcreditcardholder,etc.)
? Clustering:dataapproachusedtodivideindividuals(likecustomers)intogroups(orclusters)inausefulormeaningfulway.
o Heatmapcouldbeusedtodetermineifpurchasesareoutsideoftheperson's"home"region
? Datareduction:Adataapproachusedtoreducetheamountofinformationthatneedstobeconsideredtofocusonthemostcriticalitems(i.e.,highestcost,highes
溫馨提示
- 1. 本站所有資源如無(wú)特殊說(shuō)明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請(qǐng)下載最新的WinRAR軟件解壓。
- 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請(qǐng)聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶(hù)所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁(yè)內(nèi)容里面會(huì)有圖紙預(yù)覽,若沒(méi)有圖紙預(yù)覽就沒(méi)有圖紙。
- 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
- 5. 人人文庫(kù)網(wǎng)僅提供信息存儲(chǔ)空間,僅對(duì)用戶(hù)上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理,對(duì)用戶(hù)上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對(duì)任何下載內(nèi)容負(fù)責(zé)。
- 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容,請(qǐng)與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時(shí)也不承擔(dān)用戶(hù)因使用這些下載資源對(duì)自己和他人造成任何形式的傷害或損失。
最新文檔
- 2026浙江杭州市西湖區(qū)大禹路幼兒園誠(chéng)聘幼兒教師(非事業(yè))1人備考題庫(kù)參考答案詳解
- 2026福建三明尤溪縣第二實(shí)驗(yàn)幼兒園招聘?jìng)淇碱}庫(kù)參考答案詳解
- 2026福建三明市建寧縣縣屬?lài)?guó)有企業(yè)招聘正式職工7人備考題庫(kù)完整參考答案詳解
- 2026黑龍江大興安嶺地區(qū)加格達(dá)奇區(qū)交通運(yùn)輸局基層公共服務(wù)崗公益性崗位招聘4人備考題庫(kù)及答案詳解(奪冠系列)
- 2026湖北武漢蔡甸區(qū)公立學(xué)校招聘初中教師8人備考題庫(kù)及答案詳解一套
- 2026貴州貴陽(yáng)南明綠洲清源環(huán)境監(jiān)測(cè)有限公司招聘?jìng)淇碱}庫(kù)及答案詳解(易錯(cuò)題)
- 技術(shù)項(xiàng)目管理及創(chuàng)新激勵(lì)平臺(tái)
- 康復(fù)科醫(yī)院感染管理制度
- 設(shè)備保養(yǎng)與安全生產(chǎn)結(jié)合手冊(cè)
- 數(shù)據(jù)分析師工作輔助模板包
- 醫(yī)院保安考試試題及答案
- 家校合力+護(hù)航高考+-2025-2026學(xué)年高三下學(xué)期新年開(kāi)學(xué)家長(zhǎng)會(huì)
- 文旅局安全生產(chǎn)培訓(xùn)課件
- 2026年及未來(lái)5年中國(guó)化妝品玻璃瓶行業(yè)市場(chǎng)深度分析及發(fā)展趨勢(shì)預(yù)測(cè)報(bào)告
- T-CCCTA 0056-2025 纖維增強(qiáng)納米陶瓷復(fù)合卷材耐蝕作業(yè)技術(shù)規(guī)范
- 孕婦營(yíng)養(yǎng)DHA課件
- 2025年湖北煙草專(zhuān)賣(mài)局真題試卷及答案
- 2025-2026學(xué)年廣東省廣州113中學(xué)八年級(jí)(上)期中語(yǔ)文試卷
- 飛行機(jī)組失能的處置
- GB/T 5276-2015緊固件螺栓、螺釘、螺柱及螺母尺寸代號(hào)和標(biāo)注
- GB/T 18745-2006地理標(biāo)志產(chǎn)品武夷巖茶
評(píng)論
0/150
提交評(píng)論