spss Assignment of Data Analysis.docx

spss Assignment of Data Analysis.docx

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spssAssignmentofDataAnalysis

UniversityofGlamorgan

MScManagementandDevelopmentofInternationalFinancialSystems

Module:

TechniquesofDataAnalysisforFinancialMarkets

Assignment:

StatisticalStudy

To:

UniversityofGlamorgan

From:

StudentNumberXXXXXXXX

Date:

XXXXXXXXXX

StatisticalResearchStudy:

AnalysingtheRelationshipbetweenEPSandGearingeitherinLeisureorPharmaceuticalIndustry

Content

1.Introduction----------------------------------------------------------------------------3

2.TheRelationshipBetweenEPSandGearing-------------------------------3

3.PopulationandRandomSampling---------------------------------------------4

4.HistogramsandTestofNormality---------------------------------------------7

4.1Histograms-------------------------------------------------------------------------7

4.2TestofNormality----------------------------------------------------------------8

5.CorrelationAnalysis------------------------------------------------------------------9

5.1Formulatehypotheses-----------------------------------------------------------9

5.2ScatterPlots-----------------------------------------------------------------------10

5.3Spearman’sRankOrderCorrelation--------------------------------------11

6.DifferencesAnalysis-----------------------------------------------------------------12

6.1Formulatehypotheses-----------------------------------------------------------12

6.2TestofNormalityforDifferencesAnalysis-----------------------------12

6.3Mann-WhitneyUTest----------------------------------------------------------13

7.Limitations--------------------------------------------------------------------------------13

8.Conclusion--------------------------------------------------------------------------------14

References-----------------------------------------------------------------------------------15

1.Introduction

Itiswidelyacceptedthatearningpershare（EPS）isimportanttothecorporatefinancialdecisions（DavidsonandMallin,1998）andanychangesintheuseofdebtwouldcausechangesinEPS（Dickersonetal.,1995）.ThepurposeofthisreportistofindoutifthereisarelationshipbetweenEPSandGearingeitherinleisureorpharmaceuticalindustrythroughaseriesoftestsbySPSSandifthereis,whatleveloftherelationshipis.

Thestudyusesaquantitativeapproach.Firstly,itwillcollectdataof80companiesfromtwoindustries“Leisure”and“Pharmaceutical”whicharealllistedonLondonStockExchangeandthenget30fromeachindustryasrandomsamplesforthetests.Secondly,itwouldassessthenormalityforthesamplesbothbyhistogramsandthe“Explore”optionofSPSSandthirdlychoosetheappropriatetestofcorrelationtoworkoutifthereisarelationshipbetweenthesetwofinancialvariablesornot.Finally,itwouldtestthedifferencesbetweenthetwosectorsmeansofEPSandGearing.

Themethodologyusedtoanswertheresearchquestionswastoselectanappropriatestatisticalpackage（SPSSused）,runappropriatestatisticaltestsandinterpretresultsinaclearandconciseformat.

2.TheRelationshipBetweenEPSandGearing

Gearingoccurwhenabusinessisfinanced,atleastinpart,bycontributionsfromoutsideparties.Thelevelofgearingassociatedwithabusinessisoftenanimportantfactorinassessingrisk（AtrillandMcLaney,2001）.EPSistheportionofacompany'sprofitallocatedtoeachoutstandingshareofcommonstock.Itservesasanindicatorofacompany'sprofitability.Earningpershareisgenerallyconsideredtobethesinglemost importantvariableindeterminingashare'sprice.SuchasEPSandGearing,thesefinancialvariablesareveryimportantincorporatefinancialdecisions.Forexample,capitalchoicesarebasedonthetrade-offbetweenEPSandthecapitalgearingofthefirm（DavidsonandMallin,1998）.Naturally,thehighergearingwillbringboththeriskierdebtandhigherexpectedearnings（Dickersonetal.,1995）.However,theremaybedifferentsituationsamongthedifferentindustriesandadditionallyexcessivelevelsofgearingareoftenresponsibleforcorporatefailure（PikeandNeale,1996）.Thereby,itisverynecessarytodoresearchontherelationshipbetweenEPSandGearingespeciallywhenfirmsneedtoconsiderthemasimportantelementsforcapitaldecisions.

3.PopulationandRandomSampling

Apopulationisthetotalcollectionofelementswhichisusedduringthetests（Blumberg,2005）.Inthisreport,allthe80selectedcompaniesarelistedontheLondonStockExchangeand40ofthosecompaniesarefrom“Leisure”industrywhiletheothersarefrom“Pharmaceutical”withthedataoftwofinancialvariablesEPSandGearing,additionally,ithasbeencheckedthattherearenoerrors（e.g.missing）indatafiles.

Usually,itisassumedthattheselectionreflectsthecharacteristicsofthefullset（Blumbergetal.,2005）andthereforetherandomsamplingistheinfluentialstepofthewholeprocessandtheeveryelementsofthepopulationshouldhaveaknown,non-zeroprobabilityofbeingincludedinthesample（Gillbert,D.etal,2004）.Accordingly,30companiesarerandomlychosenfromeachsectorbySPSSandhasbeenarrangedinascendingorderbyvariableEPS.Thesamplesfromtwoindustriesafterrandomareidentifiedintable1and2respectively.

Table1:

LeisureIndustryRandomSamples

Table2:

PharmaceuticalIndustryRandomSamples

4.HistogramsandTestofNormality

Manyofthestatisticaltechniques（e.g.parametricstatistics）assumethatthedistributionofscoresonthedependentvariableis“normal”（Pallant,2005）.Inotherwords,ifthedistributionofscoresisnotnormal,itneedstochoosedifferentstatisticalteststoanalyseissuessuchascorrelation,differencesbetweenvariables.Asaresult,testofnormalityisoneofthemostimportantstepsinthewholetestsanditcanbeassessedbothbyhistogramandtheExploreoptioninSPSS.

Histograms

AsGravetterandWallnau（2000,pp52）indicated,normalisusedtodescribeasymmetrical,bell-shapednormalcurve,whichhasthegreatestfrequencyofscoresinthemiddle,withsmallerfrequenciestowardstheextremes.

Figure1:

Figure2:

HistogramofEPSin“Leisure”HistogramofGearingin“Leisure”

Figure3:

Figure4:

HistogramofEPSin“Pharmaceutical”HistogramofGearingin“Pharmaceutical”

Figure1and3displaythedistributionsofEPSin“Leisure”and“Pharmaceutical”andtheothertwofiguresexhibitthedistributionofGearingin“Leisure”and“Pharmaceutical”separately.Byobservingthenormalcurveandfrequencyinthose4histograms,itcouldeasilyfindthatthescoresinfourfiguresareallskewedtotheleftandmostscorearenotoccurringinthecentre,taperingouttowardstheextremes,althoughitseemsthatthetwocurvesofEPSandGearingin“Pharmaceutical”alittlebitmorenormalthanthatofthemin“Leisure”.Inordertocertifythattheyareexactlyunnormaldistributed,itneedstotaketestbyExploreoptioninSPSS.

TestofNormality

TheresultsofTestofNormalityaregivenbytheKolmogorov-SmirnovstatisticanditindicatesnormalitywhentheSig.valueismorethan.05（Pallent,2005）.AsTable3indicatesthattheSig.values（referto0.002,0.006,0.000,and0.000）arealllessthan.05,thereforethescoresofEPSandGearingeitherin“Leisure”or“Pharmaceutical”arenotnormallydistributed.

Table3:

ThetestofNormalityofEPSandGearingintheTwoSectors

5.CorrelationAnalysis

“Correlationanalysisisusedtodescribethestrengthanddirectionofthelinearrelationshipbetweentwovariables.”（Pallant,2005,pp121）Inthisreport,itneedstoworkoutifthereisarelationshipbetweenEPSandGearingeitherin“Leisure”or“Pharmaceutical”ornot.

Accordingtotheresultoftestofnormalityabove,itdemonstratesthatallthescoresareunnormallydistributed.Therefore,thiscorrelationanalysisneedstotake“Spearmanrankordercorrelation”whichbelongstonon-parametrictechniques.Althoughnon-parametrictechniquearelesspowerfulthanparametricalternative,itisalsousefulwhenthereisrelativesmallamountofsamples（e.g.N=30）andthescoresarenotnormallydistributed.

FormulateHypotheses

In“Leisure”:

Nullhypotheses（H0）:

ThereisnocorrelationbetweenEPSandGearingin“Leisure”.

Alternativehypotheses（H1）:

ThereisacorrelationbetweenEPSandGearingin“Pharmaceutical”.

IfSig.>.05,H0isacceptedbutH1isrefused;

Sig.<.05,H0isrefusedbutH1isaccepted.

In“Pharmaceutical”:

Nullhypotheses（H0）:

ThereisnocorrelationbetweenEPSandGearingin“Pharmaceutical”.

Alternativehypotheses（H1）:

ThereisacorrelationbetweenEPSandGearingin“Pharmaceutical”.

IfSig.>.05,H0isacceptedbutH1isrefused;

Sig.<.05,H0isrefusedbutH1isaccepted.

ScatterPlots

BeforedoingacorrelationtestitisagoodideatogenerateascatterplotfirsttoseethenatureoftherelationshipbetweenEPSandGearing（Pallant,2005）.

Figure5:

ScatterplotsofEPSandGearingin“Leisure”

Figure6:

ScatterplotsofEPSandGearingin“Pharmaceutical”

ThedatapointsinFigure5andFigure6showsthedifferentsituations.WhilethescatterplotsforoutlierswhichspreadallovertheplaceinFigure5suggestsaverylowcorrelationbetweenEPSandGearing,thepointsinFigure6whichareneatlyarrangedinanarrowcigarshapesuggestquiteastrongcorrelation.Thus,bycheckingthescatterplots,itsuggeststhatthereisasmallrelationshipofEPSandGearingin“Leisure”,nevertheless,thereisasignificantrelationshipofthesetwovariablesin“Pharmaceutical”.

Spearman’sRankOrderCorrelation

Althoughthescatterplotsshow