版權(quán)說明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請進行舉報或認領(lǐng)
文檔簡介
Chapter5
DataAnalysis&DiscussionGraduateAcademicEnglishWriting
DataDelugeThankstothedigitalrevolution,everyinteraction,transactionandcommunicationgeneratesafootprint."Datadeluge"referstotheoverwhelmingincreaseintheamountofdatageneratedbyvariousdigitalactivities.Thisphenomenonisaconsequenceofthedigitalrevolutionandthewidespreaduseoftechnology,whichresultsinacontinuousfloodofinformationthatcanbechallengingforindividualsandorganizationstomanageefficiently.Whatisdata?Dataasaconceptcanbeviewedasthelowestlevelofabstractionfromwhichinformation,and,then,knowledgearederived.Ingeneralterms,dataisasetofvaluesofqualitativeorquantitativevariables.Thepresenceofdata,assomethingalreadyfoundorsomethingcreatedthroughresearchprocessesorasaby-productofsocialaction,isseentohavevalueeitherinitselforinitsreuse.Whatisresearchdata?Researchdataisanymaterialusedasafoundationforresearch.TheEuropeanCommission(EC)statesthatresearchdatamaybenumerical/quantitative,descriptive/qualitativeorvisual,raw,oranalyzed,experimentalorobservational.Examplesincludedigitizedprimaryresearchdata,photographsandimages,films,etc.(EuropeanCommission2012).Thus,datacanbeintheformofpublishedtexts,artifactsorrawunprocesseddata.Whatisdataanalysis?Dataanalysisistheinvestigativeprocessusedtoextractknowledge,informationandinsightsaboutrealitybyexaminingdata.Dataanalysisfocusesontheconnectionsbetweenthedata,themethod,itsresultsandreality.Dataanalysisreliesontwoexternaltools:measuredandrecordeddata,whichisanexternalrepresentationofknowledge;andlogic,particularlymathematics,whichisanexternalsystemforprocessinginformation.Dataanalysisisaninvestigativeprocesstoextractknowledgeinformationandinsightsaboutrealityfocusesonconnectionsbetweenthedatathemethoditsresultsandrealityreliesontwoexternaltools1.measuredandrecordeddata2.logicAmbiguityindataanalysisIfsmokingiscorrelatedwithlungcancer,doesthissuggestthatsmokingcauseslungcancer(schema1),thatlungcancercausessmoking(schema2)orthatathirdvariablecausesboth(schema3)?Whatdoyouthinkoftheaboveargument?Peoplesaythatwithambiguityindataanalysis,youcanneverbesurethatsmokinghascausedlungcancer.Supposeitistrue,whatotherevidenceisneeded?Exploratorydataanalysis(EDA)EDAisconcernedwithobservationaldatamorethanwithdataobtainedbymeansofaformaldesignofexperimentswithaviewtoforminghypotheses.Ageneralizedexploratorytaskproceedsasfollows:a.Fitatentativemodeltoavailabledata.b.Identifydifferencesbetweenthemodelanddata.c.Judgewhetherthedifferencessuggestthatthemodelismisfit,over-fitorunder-fit(discrepancies).d.Retainorrefinethemodelasnecessary.e.Selectaplausibleschemathatinterpretsthemodelinthecontextoftheresearch.ConfirmatoryDataAnalysisConfirmatorystatisticsconsistsofexperimentaldesign,significancetesting,estimationandprediction.Ageneralizedconfirmatorytaskproceedsintheoppositedirection:a.Selectanappropriateschematoguidedatacollection.b.Deduceaprecisehypothesisfromtheschema.Multiplehypothesesmaybedevelopedtotestmultipleaspectsoftheschema.c.Identifythesetofdatathatwouldberelevantfortestingthehypothesis.d.Collectarepresentativesubsetofthedata.e.Identifydifferencesbetweendataandthehypothesis.f.Judgewhetherthediscrepanciesimplymeaningfuldifferencesbetweenthehypothesisandrealityorresultfromrandomvariationorfaultydata.g.Confirm,updateorrejectthehypothesizedmodel(anditsassociatedschema).CDAproposedbyChatfieldin1995(1)Understandtheproblemandclarifyobjectives(beginwithaschema).(2)Collectdatainanappropriateway(collectdata).(3)Assessthestructureandqualityofthedata,thatis,cleanthedata.(4)Examineanddescribethedata(transformdataintowords,visuals,etc.).(5)Selectandcarryoutappropriatestatisticalanalyses:(a)Lookatdata(transformintovisuals).(b)Formulateasensiblemodel(makeschemaprecise).(c)Fitthemodeltothedata(fitmodel).(d)Checkthefitofthemodel(identifydiscrepancies).(e)Utilizethemodelandpresentconclusions.(6)Comparefindingswithfurtherinformation,suchaspreviousfindings(iterate).(7)Interpretandcommunicatetheresults.Pleasereadthesampleinthischapter.CouldyoutellmewhetherthesampleofthedataanalysisinthischapterisEDAorCDA?Why?BiasesinDataAnalysisFirstofall,dataanalysisisbiasedtowardsacceptedschemas.Schemasdeterminewhereattentionwillbeplacedandhowobservationswillbeinterpreted.Informationthatcontradictsaschemaislesslikelytobenoticed,correctlyinterpreted,orrecalledlater.WhydidtheseasonaldropsofozoneconcentrationsoverAntarcticagounnoticedforyears?BiasesinDataAnalysisAnotherwell-knownbiasindataanalysisisunsoundlogicalconnections.IfschemaPistrue,datashouldlooklikeQ.ThedatalookslikeQ.Therefore,schemaPistrue.Istheaboveinferencelogical?Whyorwhynot?EthicsofdataanalysisResearchersmayinfluencethedatathroughfourways:a.thegenerationofresearchquestions;b.theprocessofresearchdesign,c.themonitoringofdatacollection,d.theprocessofdataanalysis.Violationsofethicalprinciplesintheanalysisofdata,likefalsificationandmisinterpretationofresults,leadtoadditionalnoise.Ethicalconsiderationsinvolvethreeaspects:
ThecollectionorselectionofdataThepresentationordescriptionofdataTheformationofinterpretationsandconclusionsPrinciplesofdataanalysisAccordingtotheAmericanStatisticalAssociation(ASA),theroleofthestatisticianortheroleofthedataanalysisisideallyneutral.ASAhasformulatedfiveprinciplesfordataanalysis:a.Theresultsandfindingsofresearchshouldbepresentedhonestlyandopenly.Thesuppressionofcontradictoryfindingsistobeavoided.b.Deceptiveoruntruestatementsinresearchreportsshouldbeavoided.c.Theboundariesofinferenceshouldbeclearlydelineated.Suchboundariesmayincludeconsiderationsofthesamplingofsubjectsandlevelsofindependentvariablesexaminedintheresearch.d.Clearandcompletedocumentationofdataediting,statisticalprocedures,andassumptionsshouldbeprovided.e.Statisticalproceduresshouldbeappliedwithoutconcernforafavorableoutcome.Considertheresearchquestionofyourownoryoursupervisor’sresearch.Oryoucanjustreadaresearchpaperandconsideritsresearchquestion.Doyouneeddatatoansweryourresearchquestion?Whyorwhynot?Doesyourresearchquestioninfluencethewayyoucollectandanalyzedata?Inwhatways?AnalyzethesamplePleasereadthesampleanddiscusshowdataiscollected.Howdoyoucollectdataforyourresearch?surveyexperimentorpseudo-experimentlabtestobservationfieldnotesvideo-recordinginternetdatabigdatainterviewsSo,howdoyoucollectdataforoneofyourparticularresearch?AnalyzethesampleHowisdataanalyzedinthesample?Howdoyouanalyzedata?Doyouhaveahypothesis?IsyoursCDAorEDA?Doyouuseaninstrument?Doyouuseasoftware?DoyouuseAI?Doyouneedtovalidateyouranalysis?Howdoyouvalidateyouranalysis?Haveagroupdiscussionandsharewitheachotheryourmethodofdatacollectionandanalysis.DataVisualizationLookatthefollowingtwoformsofdatapresentaton,andconsider:doesthetablemakeanydifferencesinaresearchpaper?In1996,onaverage,menearned$32,144ayear,women$23,710,adifferenceof
8,434.Table5.1.male-femalesalaries($)1996Men32,144Women23,710Difference8,434
AnalyzethesamplePleasereadthesample,inparticular,discusshowdataisvisualizedinthetext.Doyoulikeit?Isitgoodinyoureyes?Whyorwhynot?DatavisualizationBetween1970and2000,thestructureoffamilieschangedintwoways.In1970,85percentoffamilieshadtwoparents,butin1980thatnumberdeclinedto77percent,thento73percentin1990,andto68percentin2000.Thenumberofone-parentfamiliesrose,particularlyfamiliesheadedbyamother.In1970,11percentoffamilieswereheadedbyasinglemother.In1980thatnumberroseto18percent,in1990to22percent,andto23percentin2000.Singlefathersheaded1percentofthefamiliesin1970,2percentin1980,3percentin1990,and4percentin2000.Familieswithnoadultinthehomehaveremainedstableat3-4percent.Pleasereadtheaboveparagraph,andcreateagraphtovisualizethedataherein.EthicalConsiderationsinDataVisualizationDatashouldbepresentedandvisualizedclearly,accurately,relevantly,andinparticular,honestly.Thefollowingtipsshouldbeheeded:Donotdistortdataortheirrelationshiptomakeapoint.Donotimplyfalsecorrelations.Donotmanipulateascaletomagnifyorreduceacontrast.Donotmakeatableorfigureunnecessarilycomplexormisleadinglysimple.Theimageshouldnotencouragereaderstomisjudgevalues.Ifthetableorfiguresupportsapoint,stateit.DatapresentationsinOlympics:Whatdoesitsayaboutnationalpride?China’smedaltableDatapresentationsinOlympics:Whatdoesitsayaboutnationalpride?Europe’smedaltableDatapresentationsinOlympics:Whatdoesitsayaboutnationalpride?Australia’smedaltableDatapresentationsinOlympics:Whatdoesitsayaboutnationalpride?WhatdidtheUSmediadotoensurethattheUSAstaysontopofthemedaltableduringtheTokyoOlympicGames?PleaseanalyzethedifferentdatapresentationsandformaclaimabouttherelationshipbetweennationalprideandOlympicmedaltableformulation.
Whatdoesitsayaboutdatapresentation?
DatadiscussionAdatadiscussion
hasarelativelyfixedstructurecontainingusuallytheelementsinthefollowingorder:Locationelementsand/orsummarystatementsHighlightingstatementsDiscussionsofimplications,problems,exceptions,etc.AnexampleofdatacommentaryLocation+indicativesummary
linkingasclauseTable5
showsthemostcommonmodesofinfectionforU.S.businesses./Ascanbeseen,inthemajorityofcases,thesourceofviralinfectioncanbedetected,withdisksbeingbroughttotheworkplacefromhomebeingbyfarthemostsignificant.(highlight1)However,itisalarmingtonotethatthesourceofnearly30%ofviralinfectionscannotbedetermined.(highlight2)Whileitmaybepossibletoeliminatehome-to-workplaceinfectionbyrequiringcomputeruserstorunantiviralsoftwareondiskettesbroughtfromhome,businessesarestillvulnerabletomajordataloss,especiallyfromunidentifiablesourcesofinfection.(implications)HighlightingstatementsThecentralsectionsofdatacommentariesaremadeofhighlightingstatements,whicharegeneralizationsdrawnfromthedetailsofthedatadisplay.Highlightingstatementsrequiregoodjudgementandintelligencetospottrendsorregularitiesinthedata,toseparatemoreimportantfindingsfromlessimportantones,andmakeclaimsofappropriatestrength.Inmakinghighlightingstatements,itisnecessary:tohighlighttheresults,toassessstandardtheory,commonbeliefs,orgeneralpracticeinthelightofthegivendata,tocompareandevaluatedifferentdatasets,toassessthereliabilityofthedataintermsofthemethodologythatproducedit,todiscusstheimplicationsofthedata.CreateaninsightandmakeaclaimbasedonthedataDonotsimplyrepeatthedataexpressedinnon-verbalform,ortodescribethedataratherthandiscussit.Comparethefollowingstatementsandconsiderwhichoneisbetter.Fifty-sixpercentofgirlsreportedrestrictionsongoingoutlateatnightasopposedto35%ofboys.Moregirlsreportedrestrictionsongoingoutlateatnightthandidboys.Twenty-onepercentmoregirlsreportedrestrictionsongoingoutlateatnight.ConsiderthedifferentwaysnationspresentthemedalrankinglistintheOlympics.Makeaclaimaboutit.UnjustifiableconclusionsThestrengthofclaim
indicateshowmuchtheauthoriscommittedtoanargument.Theauthorshouldbecautiousandsometimescriticalaboutthedata.Suchcautionshouldbeexpressedlinguistically.Inotherwords,itisadvisabletoqualifyormoderateclaimsmadeinaresearchpaper.Thereareseveralwaysforthispurpose:
strongreportingverbs,probability,distance,generalization,combinedqualifications.ReportingverbThewordshowingthestrongestclaimmightbe“caused”,referringtoanexplicitanddefiniteone-on-onecausalrelationship.Thephraseshowingaverystrongstrongclaimandyetnotasstrongas“caused”mightbe“contributedto”,asitreferstoanexplicitanddefiniteandyetnotone-on-onecausalrelationship.Thestrengthofclaimof“contributedto”issimilartothatof“wasoneofthecausesof”.Thecausalrelationshipofthethreeexpressions--caused,contributedto,andwasoneofthecausesof--
isstraightforwardandthereisnodoubtaboutitatall.
Pleasefillintheblankusingareportingverbandtrytoidentifyitsstrengthofclaim.DeregulationoftheU.S.bankingindustry__________the1989-1991bankingcrisis.Nowpleaseuse“probability”tofillintheblank.TherearemanywaystoexpressprobabilityinwrittenacademicEnglish.Thesimplestisthemodalauxiliary.Theexpressionsallowingsomeroomfordoubtinclude“may”and“probably”etc.,whichareusedtogetherwiththeabovereportingverbstoweakenthestrengthofclaim.Thus,“contributedto”isreplacedwith“mayhavecontributedto”,and“wasoneofthecausesof”isreplacedwith“wasprobablyoneofthecausesof”.DeregulationoftheU.S.bankingindustry__________the1989-91bankingcrisis.DistanceSuchexpressionsas“seem”and“appear”wouldleavetheimpressionthattheclaimisnotstrong,thusaddingdistancetoastrongandpossiblyunjustifiedclaim.Therearestillsomeotherwaystodothis.Forexample,“accordingtothispreliminarystudy”,“onthelimiteddataavailable”wouldcertainlyservewellhere.DeregulationoftheU.S.bankingindustry__________the1989-91bankingcrisis.Qualifyingordefendingageneralization(1)Atypicalwordforqualifyingordefendingageneralizationistheverbphrase“tendto”.Seethefollowingtwosentencesforinstance.Consumershavelessconfidenceintheeconomy.Consumerstendtohavelessconfidenceintheeconomy.Canyouqualifyaclaimbyusingthephrase“tendto”?Qualifyingordefendingaclaim(2)Anotherwaytodefendageneralizationistoqualifythesubject.Seethefollowingforillustration.Manyconsumershavelessconfidenceintheeconomy.Amajorityofconsumershavelessconfidenceintheeconomy.Inmostpartsofthecountry,consumershavelessconfidenceintheeconomy.Consumersinmostincomebracketshavelessconfidenceintheeconomy.Canyouqualifyaclaimbyqualifyingthesubject?Qualifyingordefendingaclaim(3)Athirdmethodistoaddexceptions,excludingthecounterexamples.Forexample,Withtheexceptionofafewoil-richstates,nationaleconomiesinAfricaarenotlikelytoimprovegreatlyoverthenextdecade.Canyouqualifyaclaimbyaddingexceptions?Youcanalsocombinetheabovemethodstoqualifyaclaim.Oneofthepossible“confidentlyuncertain”highlightingstatementsmightbelikethefollowing:Thedatainthissimulationstudysuggestthatinsomecircumstancestheuseofseatbeltsmayreducecertaintypesofphysicalinjuriesincaraccidents.Nevertheless,itshouldbenotedthattheabovehighlightingstatementisnotsoinformativeafterall.Dataanalysisshouldyieldvaluableinsightsandspecificresults,thussuchexpressionsas“some”or“certain”needtobeavoided.Itshouldbeourpurposeasaresearchertoclarifywhatitisexactly.AnalyzethesamplePleasereadthesample,andanalyzethedatacommentaryanditsstructure.Inwhichpartisthedatacommentarylocated?Howisitstructured?HowtoConcludeDataDiscussionConcludingdatadiscussionrequiresoriginalthinking.Theauthorshavetobelievethattheyhavesomethingworthsayingbasedonthedata.Topositiontheauthorsasknowledgeableandcapable,considerincludingsomeofthefollowingelementsintheconclusion:Explanationsand/orimplicationsofthedata(usuallyrequired)Explanationofthereasoningprocessthatledtotheconclusion(ifappropriate)Unexpectedresultsorunsatisfactorydata(ifnecessary)Possiblefurtherresearchorpossiblefuturepredictions(ifappropriate)MovesconcerningdataareoftenincludedintheMethodsectionMethodsMove1:Contextualizingthestudymethods Step1-Referencingpreviousworksand/or
Step2-Providinggeneralinformationand/orStep3-Identifyingthemethodologicalapproachand/orStep4-Describingthesettingand/or Step5-Introducingthesubjects/participantsand/or Step6-Rationalizingpre-experimentdecisions Move2:Describingthestudy
Step1-Acquiringthedataand/or
Step2-Describingthedataand/or
Step3-Identifyingvariablesand/or Step4-Delineatingexperimental/studyproceduresand/orStep5-Describingtools/instruments/materials/equipmentand/orStep6-Rationalizingexperimentdecisionsand/or Step7-ReportingincrementalsMove3:Establishingcredibility Step1-Preparingthedataand/or Step2-Describingthedataanalysisand/or Step3-Rationalizingdataprocessing/analysisDatacommentary/discussionisoftenincludedintheResultspart.ResultsMove1:Approachingtheniche
Step1-providinggeneralorientationand/or Step2-restatingstudyspecificsand/or Step3-Justifyingstudyspecifics Move2:Occupyingtheniche Step1-Reportingspecificresultsand/or Step2-IndicatingalternativepresentationofresultsMove3:Construingtheniche Step1-Comparingresultsand/or Step2-Accountingforresultsand/or Step3-Explicatingresultsand/or Step4-Clarifyingexpectationsand/or Step5-Acknowledginglimitations
Move4:Expandingtheniche Step1-Generalizingresultsand/or Step2-Claimingthevalueand/or Step3-Notingimplicationsand/or Step4-Proposingdirections
DataanalysisanddiscussionareoftenfoundintheDiscussionpart.Discussion/ConclusionMove1:Re-establishingtheterritory Step1-Drawingonatheoreticalgeneralbackgroundand/orStep2-Drawingonstudy-specificbackgroundand/or Step3-Highlightingprincipalfindingsand/or Step4-Previewingthediscussion‘roadmap’ Move2:Framingthenewknowledge Step1-Explicatingresultsand/or Step2-Accountingforresultsand/or
Step3-Clarifyingexpectationsand/or Step4-Addressinglimitations Move3:Reshapingtheterritory Step1-Supportingwithevidenceand/or Step2-Counteringwithevidence Move4:Establishingadditionalterritory Step1-Generalizingresultsand/or Step2-Claimingthevalueand/or Step3-Notingimplicationsand/or Step4-Proposingdirections
TipsforwritingtheDiscussionsectionDiscussion,asthesoulofanacademicpaper,isoneofthemostdifficultsectionstowrite.Theauthorisexpectedtoprovideaconcisereportoftheresearchfindings,andexplorethereasonsforexpectedorunexpectedresults,andhighlightinnovationsornewinsightsthroughanalysisandcomparisonofexistingresearch,andproposetheacademicvalueandapplicationprospectbasedonacknowledgedfacts.Whichpartofaresearchpaperismostdifficulttowriteandwhy?JamesHartley’sproposalaboutDiscussionwriting:JamesHartleyproposesfivestepsinwritingit:
溫馨提示
- 1. 本站所有資源如無特殊說明,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,請聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁內(nèi)容里面會有圖紙預覽,若沒有圖紙預覽就沒有圖紙。
- 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. 人人文庫網(wǎng)僅提供信息存儲空間,僅對用戶上傳內(nèi)容的表現(xiàn)方式做保護處理,對用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對任何下載內(nèi)容負責。
- 6. 下載文件中如有侵權(quán)或不適當內(nèi)容,請與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準確性、安全性和完整性, 同時也不承擔用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。
最新文檔
- 招投標法規(guī)解讀與合同管理
- 現(xiàn)金流管理與投資決策
- 工業(yè)園區(qū)物業(yè)后勤人員聘用合同
- 離婚調(diào)解書男方離婚協(xié)議
- 辦公樓變電所節(jié)能操作規(guī)程
- 畜牧業(yè)飼料儲備倉租賃合同
- 證券交易所有線電視布線合同
- 塑料制品零星施工合同
- 化工原料招投標與合同履約分析
- 制藥業(yè)原料攪拌罐建造合同
- 中學文化地理興趣社章程及考評細則(共5頁)
- 小學二年級上冊音樂-第6課《小紅帽》--人音版(簡譜)(15張)ppt課件
- 槽鋼表面積對照表
- 稀土發(fā)光材料ppt
- 鐵路物資管理模擬考試試題
- 初中歷史課堂教學如何體現(xiàn)學生的主體地位
- 部編版三年級上冊語文課件-習作六:這兒真美---(共19張PPT)部編版
- 2020湖南湖南省建筑施工開工安全生產(chǎn)條件承諾書
- 《白內(nèi)障》PPT課件.ppt
- 先進先出(FIFO)
- 2020年四年級上冊語文素材-全冊課文梳理(1-27課)-人教(部編版)全冊可修改打印
評論
0/150
提交評論