醫(yī)學(xué)統(tǒng)計(jì)學(xué)英文課件CH01-introdu課件

PostgraduatebooksrecommendedbyDegreeManagementandPostgraduateEducationBureau,MinistryofEducationMedicalStatistics(the2ndedition)

PostgraduatebooksrecommendedArrangement:total72classhours,twoclasseseachweekArrangement:total72classho

chapter1IntroductionKeydefinitionsthestepsformedicalstatisticsBriefhistoryofStatisticschapter1IntroductionStatisticsThesciencefordatacollection,sorting,andanalysis.

Statistics

Definition：thesciencethatstudythecollection,sortingandanalysisofmedicaldata.

Characteristics：

1、Usingthequantitytoreflectthequality2、Usingchanceevents(uncertainty)toreflecttheinevitability(rules)MedicalStatisticsDefinition：thescLearningobjectives：1、BasicprinciplesandmethodsofStatistics（LearningEmphasis）

2、ApplicationStatistics——(ClinicalMedicine,PreventiveMedicine,andHealthCareManagement)MedicalStatisticsLearningobjectives：MedicalStPurpose：atoolformedicalresearchEmphasis:statisticalindicatorsusedforcalculatingorcomparingthequantitativecharacteristicsofpopulationExample:healthexpectation

infantmortalityMedicalStatisticsPurpose：atoolformedicalresSection1.KeydefinitionsSection1.KeydefinitionsⅠvariable,individual,sampleandpopulationⅠvariable,individual,sampleindividual（observatoryunit）：thebasicunitinstatisticalresearch,itdependsonthepurpose.variable（indicator）：individualcharacteristics

examples:height、weight、gender、bloodtype、treatmenteffectetc.individual（observatoryunitVariablevalue：thevalueofvariablesExamples:height1.65metersweight52kggenderfemalebloodtype“O”laboratorytestnegativetreatmenteffectbetterData:composedofalotofvariablevalues.

Example:DataforbloodglucoseVariablevalue：thevalueofvahomogeneity：commoncharacteristicsforthegivenindividuals

example：theheightsoftheboyswiththeageof7livinginChangsha2004variation:differenceexistingamongthevariablevaluesofhomogeneityindividuals

example:thedifferentheightsoftheboyswiththeageof7livinginChangsha2004homogeneity：commoncharactDefinition：thewholehomogeneityindividualsdeterminedbyspecificpurpose.example：alltheheightsofboysat7thatlivedinChangsha2004finitepopulation：thespace,timeandpopulationforaspecificpopulationhavebeenlimited.infinitepopulation：

notimeandspacelimitsforthepopulation.Suchpopulationsonlyexistinimagination,soitiscalledinfinitepopulation.populationDefinition：thewholehomogdefinition：thesetofvariablevaluesofsomeindividualssampledfromthepopulationatrandom.Example:theheightsof200boysat7fromChangsha.sampledefinition：thesetofvariableSamplingstudySampleinformation(statistic)Populationcharacteristics（parameter）inferencenote：samplingisonlythewaytogetinformation,inferringthepopulationisourpurposeSamplingstudySampleinformatiⅡ、variableanddata

Ⅱ、variableanddatameasurementdata:itisalsocalledasquantitativeornumericaldata.Itsvalueisquantitative.Measurementdataalwayshasmeasurementunits.

example：heightdata,weightdatameasurementdata:itisals

enumerationdata:qualitativeorcountdata.Forsuchdata,itneedstoclassifytheobservationunitsbeforeandcountthem.Itsvalueappeardifferentcharacteristicsandsorts.Binomial:gender,liveordeath,yesorno.Multiple：bloodtype,A、B、O、AB.enumerationdata:qualitativrankeddata:ordinalorsemi-quantitativedata.Itneedtoclassifyobservatoryunitsintodifferentclassesaccordingtheextentbeforecalculatethefrequenciesofeachgroups.Thereexistsobviousdifferencesamongdifferentclasses.example:toevaluatethetreatmenteffectofonedrugonheartfailure,weusetheindicator(cured,better,worsen,dead)toassessthetreatmenteffect.Choosingofstatisticalmethodsdependsonthedatatypetoagreatextent。

rankeddata:ordinalorseDatatransformationQuantitativedata

rankeddata（multiple）binomialdataDatatransformationQuantitativexample：WBC（1/m3）countoffivepersons：

300060005000800012000quantitativevariablelowernormalnormalnormalhigherqualitativevariable

Binomialdata:normal3persons;abnormal2personsMultiplecategorydata:lower1person;normal;3persons;higher1personexample：WBC（1/m3）countoffiveⅢerrorⅢerrordefinition：thedifferencebetweenmeasurementvalueandtruevalue.1、randerror：unstableandchangingatrandom

errorsthatcausedbyuncontrolledfactors.Commonly,randerrorsarereferredtothoseerrorsappearingduringrepeatedmeasurementsandsampling.Often,measurementerrorisextremelylowerthansamplingerror.InStatistics,samplingerroristhemainstudycontents.definition：thedifferencebetw2.Nonrandomerrorisdividedintosystematicerrorandnonsystematicerror:Systematicerror:itisproducedinexperimentandkeepsconstantorchangesaccordingcertainrules.Usually,itsreasonsareknownandcontrollable.Nonsystematicerror（grosserror）:itisalwayscausedbyobviousgrosses.2.NonrandomerrorisdividedⅣ、frequencyandprobabilityⅣ、frequencyandprobability

1．Frequency

Giventhesamecondition,repeatatrialforntimesindependently.Amongntrials,Aappearsformtimes，sotheratioofm/niscalledthefrequencyofrandomeventAamongntrials.

1．Frequency

2．probability:thelikelihoodofrandomevents.Giventhesamecondition,repeatatrialforntimesindependently.Amongntrials,Aappearsfor

times，sotheratioof

iscalledthefrequencyofrandomeventA.Asnincreasesgradually,thefrequency

willapproachaconstant.TheconstantiscalledtheprobabilityofrandomeventAandexpressedin.Incommon,itisabbreviatedas.2．probability:theRange：Range：

Frequencyisusedtodescribethesample,whiletheprobabilityforthepopulation.m/nistheestimationof.Astrialsincreases,theestimationvalueismorereliable.醫(yī)學(xué)統(tǒng)計(jì)學(xué)英文課件CH01-introdu課件smallprobabilityevent:Becausetheconclusionsaremadebasedonacertainsignificancelevel,statisticiansalwaysselectasjudgecriterion.Sosucheventswitharecalledsmallprobabilityevents.Itmeansthatsucheventshappenrarelyandcanberegardedasnonoccurrence.smallprobabilityevent:Be

Section2thestepsforstatisticalwork

Section2thestepsforstHere,itmeansstatisticaldesign,themostimportantfactorforasuccessfulresearch.

Itinvolvesthearrangementsfortheprocessofdatacollection,sortingandanalysis.Ⅰdesign

Here,itmeansstatisticaldes

3．controlThreeprinciplesforexperimentdesign1．randomization2.Replication3．controlThreeprinciplobjective：togatheraccurateandreliablerawdata

datasources：

①statisticalreporting

②routinerecords

③purposivesurveysorexperiments

④statisticalyearbookandspecialdatabook

requirements：1、randomization

2、sufficientsamplesizeⅡDatacollectionobjective：togatheraccurateaⅢ．DatasortingItistheprocessthatcleansandsystematizesrawdata.Datasortingpreparestherequireddatafornextstep,dataanalysis.Ⅲ．DatasortingItistheprocesⅣData/statisticalanalysisobjective：toillustratetheruleshiddeninthedata.

Itincludestwoaspects:1.statisticaldescription：itistheprocessofdescribingthecharacteristicsofdatausingstatisticalindicators,statisticalchartsandstatisticaltables.

2.statisticalinference：theprocessofusingsamplestatistictoinferpopulationparameter.Itconsistsof:parameterestimationandhypothesistesting.

ⅣData/statisticalanalysisStatisticaldescriptionStatisticalinferenceindicatorTableandchartParameterestimationHypothesistestingStatisticalanalysisStatisticalStatisticalindicaThanks!Thanks!后面內(nèi)容直接刪除就行資料可以編輯修改使用資料可以編輯修改使用資料僅供參考，實(shí)際情況實(shí)際分析后面內(nèi)容直接刪除就行主要經(jīng)營(yíng)：課件設(shè)計(jì)，文檔制作，網(wǎng)絡(luò)軟件設(shè)計(jì)、圖文設(shè)計(jì)制作、發(fā)布廣告等秉著以?xún)?yōu)質(zhì)的服務(wù)對(duì)待每一位客戶(hù)，做到讓客戶(hù)滿(mǎn)意！致力于數(shù)據(jù)挖掘，合同簡(jiǎn)歷、論文寫(xiě)作、PPT設(shè)計(jì)、計(jì)劃書(shū)、策劃案、學(xué)習(xí)課件、各類(lèi)模板等方方面面，打造全網(wǎng)一站式需求主要經(jīng)營(yíng)：課件設(shè)計(jì)，文檔制作，網(wǎng)絡(luò)軟件設(shè)計(jì)、圖文設(shè)計(jì)制作、發(fā)感謝您的觀看和下載Theusercandemonstrateonaprojectororcomputer,orprintthepresentationandmakeitintoafilmtobeusedinawiderfield感謝您的觀看和下載TheusercandemonstrPostgraduatebooksrecommendedbyDegreeManagementandPostgraduateEducationBureau,MinistryofEducationMedicalStatistics(the2ndedition)

PostgraduatebooksrecommendedArrangement:total72classhours,twoclasseseachweekArrangement:total72classho

chapter1IntroductionKeydefinitionsthestepsformedicalstatisticsBriefhistoryofStatisticschapter1IntroductionStatisticsThesciencefordatacollection,sorting,andanalysis.

Statistics

Definition：thesciencethatstudythecollection,sortingandanalysisofmedicaldata.

Characteristics：

1、Usingthequantitytoreflectthequality2、Usingchanceevents(uncertainty)toreflecttheinevitability(rules)MedicalStatisticsDefinition：thescLearningobjectives：1、BasicprinciplesandmethodsofStatistics（LearningEmphasis）

2、ApplicationStatistics——(ClinicalMedicine,PreventiveMedicine,andHealthCareManagement)MedicalStatisticsLearningobjectives：MedicalStPurpose：atoolformedicalresearchEmphasis:statisticalindicatorsusedforcalculatingorcomparingthequantitativecharacteristicsofpopulationExample:healthexpectation

infantmortalityMedicalStatisticsPurpose：atoolformedicalresSection1.KeydefinitionsSection1.KeydefinitionsⅠvariable,individual,sampleandpopulationⅠvariable,individual,sampleindividual（observatoryunit）：thebasicunitinstatisticalresearch,itdependsonthepurpose.variable（indicator）：individualcharacteristics

examples:height、weight、gender、bloodtype、treatmenteffectetc.individual（observatoryunitVariablevalue：thevalueofvariablesExamples:height1.65metersweight52kggenderfemalebloodtype“O”laboratorytestnegativetreatmenteffectbetterData:composedofalotofvariablevalues.

Example:DataforbloodglucoseVariablevalue：thevalueofvahomogeneity：commoncharacteristicsforthegivenindividuals

example：theheightsoftheboyswiththeageof7livinginChangsha2004variation:differenceexistingamongthevariablevaluesofhomogeneityindividuals

example:thedifferentheightsoftheboyswiththeageof7livinginChangsha2004homogeneity：commoncharactDefinition：thewholehomogeneityindividualsdeterminedbyspecificpurpose.example：alltheheightsofboysat7thatlivedinChangsha2004finitepopulation：thespace,timeandpopulationforaspecificpopulationhavebeenlimited.infinitepopulation：

notimeandspacelimitsforthepopulation.Suchpopulationsonlyexistinimagination,soitiscalledinfinitepopulation.populationDefinition：thewholehomogdefinition：thesetofvariablevaluesofsomeindividualssampledfromthepopulationatrandom.Example:theheightsof200boysat7fromChangsha.sampledefinition：thesetofvariableSamplingstudySampleinformation(statistic)Populationcharacteristics（parameter）inferencenote：samplingisonlythewaytogetinformation,inferringthepopulationisourpurposeSamplingstudySampleinformatiⅡ、variableanddata

Ⅱ、variableanddatameasurementdata:itisalsocalledasquantitativeornumericaldata.Itsvalueisquantitative.Measurementdataalwayshasmeasurementunits.

example：heightdata,weightdatameasurementdata:itisals

enumerationdata:qualitativeorcountdata.Forsuchdata,itneedstoclassifytheobservationunitsbeforeandcountthem.Itsvalueappeardifferentcharacteristicsandsorts.Binomial:gender,liveordeath,yesorno.Multiple：bloodtype,A、B、O、AB.enumerationdata:qualitativrankeddata:ordinalorsemi-quantitativedata.Itneedtoclassifyobservatoryunitsintodifferentclassesaccordingtheextentbeforecalculatethefrequenciesofeachgroups.Thereexistsobviousdifferencesamongdifferentclasses.example:toevaluatethetreatmenteffectofonedrugonheartfailure,weusetheindicator(cured,better,worsen,dead)toassessthetreatmenteffect.Choosingofstatisticalmethodsdependsonthedatatypetoagreatextent。

rankeddata:ordinalorseDatatransformationQuantitativedata

rankeddata（multiple）binomialdataDatatransformationQuantitativexample：WBC（1/m3）countoffivepersons：

300060005000800012000quantitativevariablelowernormalnormalnormalhigherqualitativevariable

Binomialdata:normal3persons;abnormal2personsMultiplecategorydata:lower1person;normal;3persons;higher1personexample：WBC（1/m3）countoffiveⅢerrorⅢerrordefinition：thedifferencebetweenmeasurementvalueandtruevalue.1、randerror：unstableandchangingatrandom

errorsthatcausedbyuncontrolledfactors.Commonly,randerrorsarereferredtothoseerrorsappearingduringrepeatedmeasurementsandsampling.Often,measurementerrorisextremelylowerthansamplingerror.InStatistics,samplingerroristhemainstudycontents.definition：thedifferencebetw2.Nonrandomerrorisdividedintosystematicerrorandnonsystematicerror:Systematicerror:itisproducedinexperimentandkeepsconstantorchangesaccordingcertainrules.Usually,itsreasonsareknownandcontrollable.Nonsystematicerror（grosserror）:itisalwayscausedbyobviousgrosses.2.NonrandomerrorisdividedⅣ、frequencyandprobabilityⅣ、frequencyandprobability

1．Frequency

Giventhesamecondition,repeatatrialforntimesindependently.Amongntrials,Aappearsformtimes，sotheratioofm/niscalledthefrequencyofrandomeventAamongntrials.

1．Frequency

2．probability:thelikelihoodofrandomevents.Giventhesamecondition,repeatatrialforntimesindependently.Amongntrials,Aappearsfor

times，sotheratioof

iscalledthefrequencyofrandomeventA.Asnincreasesgradually,thefrequency

willapproachaconstant.TheconstantiscalledtheprobabilityofrandomeventAandexpressedin.Incommon,itisabbreviatedas.2．probability:theRange：Range：

Frequencyisusedtodescribethesample,whiletheprobabilityforthepopulation.m/nistheestimationof.Astrialsincreases,theestimationvalueismorereliable.醫(yī)學(xué)統(tǒng)計(jì)學(xué)英文課件CH01-introdu課件smallprobabilityevent:Becausetheconclusionsaremadebasedonacertainsignificancelevel,statisticiansalwaysselectasjudgecriterion.Sosucheventswitharecalledsmallprobabilityevents.Itmeansthatsucheventshappenrarelyandcanberegardedasnonoccurrence.smallprobabilityevent:Be

Section2thestepsforstatisticalwork

Section2thestepsforstHere,itmeansstatisticaldesign,themostimportantfactorforasuccessfulresearch.

Itinvolvesthearrangementsforthe