SPSS的分析報告詳解

PAGEPAGE2Introductiontothedata這張數(shù)據(jù)表包含八個變量，分別是Ageinyears，Maritalstatus，Incomebeforetheprogram，Incomeaftertheprogram，Levelofeducation，Gender，Numberofpeopleinhousehold，Programstatus。通過對這些變量進行頻數(shù)分析，描述性統(tǒng)計分析，交叉分析，方差分析，參數(shù)檢驗以及相關分析，從而得出了以下結論。二．Summaryofthedata1.頻數(shù)分析基本的統(tǒng)計分析往往從頻數(shù)分析開始。通過頻數(shù)分析能夠了解變量取值的狀況，對把握數(shù)據(jù)的分布特征是非常有用的。此次分析利用的是工資狀況數(shù)據(jù)表，在性別、教育程度等不同的情況下的頻數(shù)分析，從而了解變量的取值狀況。Fundamentalstatisticanalysisbeginssometimesfromanalysisfrequentandcontinuous.Situationtakingvaluebythefactthatanalysisfrequentandcontinuousisabletoknowavariable,thecharacteristicisveryusefultothedistributiongraspingadata.Thatthisanalysismakesuseofissalarysituationdatasheet,beforesex,levelofeducationDengBuTongtheanalysisfrequentandcontinuousundercondition,choosingknowingavariabletherebyisworthstatus.StatisticsAgeinyearsLevelofeducationGenderNValid800800800Missing000圖表1首先，對原有數(shù)據(jù)中的教育程度進行頻數(shù)分析，結果如下：Firstly,carryoutanalysis,resultfrequentandcontinuousonlevelofeducationinoriginaldataasfollows:LevelofeducationFrequencyPercentValidPercentCumulativePercentValidDidnotcompletehighschool36445.545.545.5Highschooldegree28235.335.380.8Somecollege15419.319.3100.0Total800100.0100.0圖表2上表說明：被調查者中有45.5%的教育程度在高中以下，是個組中頻數(shù)最高的；其次是教育程度為高中的占35.3%；教育程度達到大學的只占到19.3%，所占比例最低，如圖表一所示，教育程度在高中以下所占面積最高，而教育程度達到大學的所占的面積最少Fixformexplanation:Quiltlevelofeducationhaving45.5%intheinvestigatorunderhighschool,bethatthegroupintermediatefrequencynumberismaximal;Bethatlevelofeducationishighschool'ssecondlyaccountfor35.3%;Thegodoftheearthwhoreachesuniversitytakesuplevelofeducationto19.3%,takenuptheproportionminimum,ifdiagramwhatoneshows,levelofeducationtakesupareamosthighlyunderhighschool,butlevelofeducationreacheswhatuniversityaccountsforareathefewest圖表三secondly,makinguseofSPSStoanalyseIncomebeforetheprogramandIncomeaftertheprogramthistwovariables,thengoalonganalysestheanalysisfrequentandcontinuous,makingAnalyseresultasfollows:IncomebeforetheprogramFrequencyPercentValidPercentCumulativePercentValid6.00293.63.63.67.0012215.315.318.98.0020325.425.444.39.0018823.523.567.810.0012015.015.082.811.00739.19.191.912.00445.55.597.413.00141.81.899.114.007.9.9100.0Total800100.0100.0圖表4圖表5以上兩張表是對incomebeforetheprogram變量的分析說明：被調查者中有收入為8元的人數(shù)占25.4%，是個組中頻數(shù)最高的的；其次是收入為9元的占23.5%；而最低的為收入18元的，占全體的1.8%。從條形圖來看，收入分不存在一定的左偏。其均值為8.9438元。Allabovetwoformsareanalyticalinstructionforincomebeforetheprogramvariable:25.4%isaccountedforbythenumberhavinginvisibleincometobe8yuanintheinvestigator,isthatthegroupintermediatefrequencynumberismaximal;Bethatinvisibleincomeis9yuansecondlyaccountfor23.5%;Butlowestbeingtakesin18yuan,Zhanentire1.8%.Thecertainleftjudgingfrombarchart,takinginmarkofnothingnessisslanting.Whosemeanvalueis8.9438yuan.而對Incomeaftertheprogram變量的分析則說明：被調查者中有收入為16元的人數(shù)占9.6%，是個組中頻數(shù)最高的的；其次是收入為17元的占9.5%；而最低收入在24~36元之間。從條形圖來看，收入分不存在一定的左偏，最高值集中在16~17元之間，其均值為16.4925元。ButanalyticaltheninstructionforIncomeaftertheprogramvariable:Beaccountedfor9.6%,bethatthegroupintermediatefrequencynumberismaximalbythenumberhavinginvisibleincometobe16yuanintheinvestigator;Bethatinvisibleincomeis17yuansecondlyaccountfor9.5%;Butminimuminvisibleincome36isbasicin24~between.Thecertainleftjudgingfrombarchart,takinginmarkofnothingnessisslanting,thepersonisworthmaximalvaluealltogetherequallyin16~between17yuan,for16.4925yuan.IncomeaftertheprogramFrequencyPercentValidPercentCumulativePercentValid7.005.6.6.68.0081.01.01.69.00192.42.44.010.00313.93.97.911.00425.35.313.112.00648.08.021.113.00637.97.929.014.00637.97.936.915.00637.97.944.816.00779.69.654.417.00769.59.563.918.00496.16.170.019.00425.35.375.320.00435.45.480.621.00415.15.185.822.00293.63.689.423.00283.53.592.924.0091.11.194.025.00141.81.895.826.007.9.996.627.00121.51.598.128.004.5.598.629.003.4.499.030.003.4.499.431.001.1.199.534.002.3.399.835.001.1.199.936.001.1.1100.0Total800100.0100.0圖表6圖表7 最后，對原有數(shù)據(jù)中的Numberofpeopleinhousehold進行頻數(shù)分析，結果如下：NumberofpeopleinhouseholdFrequencyPercentValidPercentCumulativePercentValid138548.148.148.1225231.531.579.638510.610.690.34587.37.397.55101.31.398.8691.11.199.971.1.1100.0Total800100.0100.0圖表1—8以上兩張表是對Numberofpeopleinhousehold變量的分析說明：被調查者中Numberofpeopleinhousehold為一人的占48.1%，是個組中頻數(shù)最高的的；其次是Numberofpeopleinhousehold為兩人的占31.5%；而Numberofpeopleinhousehold為七人的所占比例最低，占全體的0.1%。從條形圖來看，Numberofpeopleinhousehold存在一定的左偏。其均值為1.86人。2.描述統(tǒng)計分析在通過頻數(shù)分析把握了數(shù)據(jù)的總體分布狀況后，我們通常還需要對數(shù)據(jù)的分布特征有更為精確的認識，這就需要通過計算基本描述統(tǒng)計的方法來實現(xiàn)。下面就對各個變量進行了描述統(tǒng)計分析，得到了它們的均值、標準差、偏度、峰度等數(shù)據(jù)，以進一步準確把握數(shù)據(jù)的集中趨勢和離散趨勢。Afterthedatapopulationdistributesstatusbyhavinganalysedassurancemanytimes,werequirethatthedistributioncharacteristictothedatahasbeinganaccuratecognitionmore,themethodthatthisneedstodescribestatisticsbycalculatingbasicrightawaycomestocometruegenerally.Followinghasdescribedstatisticanalysiswithregardtohavingbeeninprogresstoeachvariables,hasgotdatasuchastheirmeanvalue,standarddeviation,slantingdegree,peakdegree,takingasanexamplegoastepfurtheraccurategraspconcentrateatrendandstragglingdatatrend.集中趨勢是指一組數(shù)據(jù)向某一中心值靠攏的傾向。計算集中趨勢可以反映數(shù)據(jù)的一般水平。均值就是反映某個變量所有取值的集中趨勢或平均水平。離散程度是指一組數(shù)據(jù)遠離中心值的程度。如果數(shù)據(jù)都緊密地集中在中心值的周圍，即數(shù)據(jù)的離散程度較??；相反，如果數(shù)據(jù)比較松散地分布在中心值的周圍，則說明數(shù)據(jù)的離散程度較大。Concentratingatrendistheinclinationpointingtoagroupofdatadrawclosetosomeonecentrevalue.Levelcalculatingthesortconcentratingatrendbeingabletoreflectdata.Meanvalueisthatthetrendortheaverageishorizontalreflectsome'svariablepossessionstakingconcentratingbeingworth.Stragglingdegreeisthedegreepointingtoagroupofdatabefarawayfromcentrevalue.Ifthedataisallrapidandintense,scatteringbeingadataaroundvalueincentre,degreeisalltogetherless;Onthecontrary,ifthedatacomparisondistributesvicinitybeingworthincentreloosely,explainthatstragglingdatadegreeisbigger.DescriptiveStatisticsAgeinyearsIncomebeforetheprogramIncomeaftertheprogramNumberofpeopleinhouseholdValidN(listwise)NStatistic800800800800800MinimumStatistic166.007.001MaximumStatistic2114.0036.007MeanStatistic18.468.943816.49251.86Std.DeviationStatistic1.3391.642854.702931.088SkewnessStatistic.088.584.6751.500Std.Error.086.086.086.086KurtosisStatistic-.845.059.6472.300Std.Error.173.173.173.173圖表8三.Exploratorydataanalysis1.交叉分析通過頻數(shù)分析能夠掌握單個變量的數(shù)據(jù)分布情況，但是在實際分析中，不僅要了解單個變量的分布特征，還要分析多個變量不同取值下的分布，掌握多個變量的聯(lián)合分布特征，進而分析變量之間的相互影響和關系。Byanalysingthedatadistributionconditionbeingabletohavesinglevariablesinhandmanytimes,butinactualanalysis,notonlyneedingtoknowthesinglevariablesdistributioncharacteristic,wantthedistributionunderanalysingmuchvariablediversitytakingvalue,tograspmuchvariableunitydistributingacharacteristic,andthentoanalyseinfluenceeachotherandrelationbetweenthevariabletoo.(1)教育程度和性別的交叉分析為了分析教育程度和性別這兩個變量之間的分布，編制了一張涉及兩個變量的二維交叉列聯(lián)表，反映了不同教育程度下性別的頻數(shù)分布情況。在下表中教育程度稱為行向量，性別稱為列向量。表格中間是觀測頻數(shù)和各種百分比。例如，教育程度在高中以下的男女人數(shù)分別是190人和174人，其所占比例分別是52.2%和47.8%。在條形圖中也可以看出女性比例高于男性比例。而教育程度為大學的男女人數(shù)分別是74人和80人，其所占比例分別是48.1%和51.9%。在條形圖中也可看出再次教育程度下男性比例高于女性比例。Therefore,havewovenatwo-dimensionalcrosscolumncoupletformrelatingtotwovariablesforanalyticallevelofeducationandthesexdistributionbetweenthistwovariables,frequentsexnumberdistributesconditionunderhavingreflecteddifferentlevelofeducation.Mymiddleformlevelofeducationiscalledthelinevector,sexiscalledthecolumnvector.Betoobservethefrequentandcontinuousandvariouspercentageinthetable.Thatforinstance,thelevelofeducationmenandwomennumberunderhighschoolpartsforis190peopleand174people,thatit'swhatistakenupproportionpartsforis52.2%and47.8%.Proportionishigherthanthemalesexproportioninalsobeingabletoperceiveafemaleinthebarchart.Levelofeducationisthatthemenandwomennumberlearningenthusiasticallypartsforis74peopleand80people,Butthatlevelofeducationisthatauniversity'smenandwomennumberpartsforis74peopleand80people,thatwhatwhosetakesupproportionpartsforis48.1%and51.9%.Inthebarchartalsoperceivethemalesexproportionisonceagainhigherthanfemaleproportionunderlevelofeducation.圖表9圖表10(2)教育程度和婚姻狀況的交叉分析為了分析教育程度和婚姻狀況這兩個變量之間的分布，編制了一張涉及兩個變量的二維交叉列聯(lián)表，反映了不同教育程度下婚姻狀況的頻數(shù)分布情況。在下表中教育程度稱為列向量，婚姻狀況稱為行向量。表格中間是觀測數(shù)。例如，教育程度在高中以下的婚否人數(shù)分別是180人和184人。在條形圖中也可以看出未婚比例高于已婚比例。而教育程度為大學的婚否人數(shù)分別是68人和86人。在條形圖中也可看出教育程度為大學下的未婚比例高于已婚比例。Maritalstatus*LevelofeducationCrosstabulationLevelofeducationTotalDidnotcompletehighschoolHighschooldegreeSomecollegeMaritalstatusUnmarriearrieotal3642821548002．單因素方差分析單因素方差分析用來研究一個控制變量的不同水平是否對觀測變量產生了顯著影響。下面我們就分別以Levelofeducation和Ageinyears這兩個變量作為控制變量，incomeaftertheprogram作為觀測變量，通過單因素方差分析方法研究Levelofeducation和Ageinyears對incomeaftertheprogram的影響進行分析。分析結果如下：Shanfactormethoddifferenceanalysisisusedtostudyanotableeffecthavingcontrolledifthevariablediversitylevelcomeintobeingtoobservingavariable.WecontrolavariableunderneathrightawayrespectivelywithLevelofeducationandAgeinyearsthistwovariablesaction,theincomeaftertheprogramistheobservationvariable,analysebythefactthatShanfactormethoddifferenceanalysismethodstudiestheimpactofLevelofeducationandAgeinyearsoverincomeaftertheprogramisinprogress.Analyseresultasfollows:Levelofeducation對incomeaftertheprogram的單因素方差分析結果ANOVAIncomeaftertheprogramSumofSquaresdfMeanSquareFSig.BetweenGroups4822.96522411.482149.580.000WithinGroups12848.99079716.122Total17671.955799圖表15Ageinyears對incomeaftertheprogram的單因素方差分析結果ANOVAIncomeaftertheprogramSumofSquaresdfMeanSquareFSig.BetweenGroups1675.9015335.18016.637.000WithinGroups15996.05479420.146Total17671.955799圖表16圖表15是Levelofeducation對incomeaftertheprogram的單因素方差分析結果?？梢钥闯觯河^測變量incomeaftertheprogram的離差平方總和為17671.955；如果僅僅考慮Levelofeducation單個因素的影響，則incomeaftertheprogram總變差中，不同Levelofeducation可解釋的變差為4822.965，抽樣誤差引起的變差為12848.990，它們的方差分別為2411.482和16.122，相除所得的F統(tǒng)計量的觀測值為149.580，對應的概率P值近似等于0.如果顯著性水平α為0.05，由于概率P值小于顯著性水平q，則應拒絕原假設，認為不同的Levelofeducation對incomeaftertheprogram產生了顯著影響，不同的Levelofeducation對incomeaftertheprogram的影響效應不全為0。Diagram15istheLevelofeducationShanfactormethoddifferenceanalysisresulttoincomeaftertheprogram.Itcanbeseen:Thedispersionsquaresumobservingthevariableincomeaftertheprogramis17671.955;IfconsideringLevelofeducationsinglefactorseffectonly,inbeingthattheincomeaftertheprogramisalwayschangedintodifference,differentLevelofeducationbutinterpretiveunexpectedturnofeventsdispatchesbeing4822.965,theunexpectedturnofeventsthattheerrorsamplingarousesdispatchesbeing12848.990,theirmethoddifferenceis2411.482and16.122respectively,isequalto0eachotherexceptthatthegainsFcountingtheamountsobservedvaluebeing149.580,correspondingprobabilityPvaluebeingsimilarwith.Shoulddeclinetheplainhypothesisthen,thinkthatdifferentLevelofeducationhasproducednotableeffecttoincomeaftertheprogram,ifthenotablelevelalphais0.05sinceprobabilityPvalueissmallerthannotablelevelq,theeffectdoesnotsatisfyfor0animpactofdifferentLevelofeducationoverincomeaftertheprogram.同理，圖表16是Ageinyears對incomeaftertheprogram的單因素方差分析結果?？梢钥吹剑喝绻麅H僅考慮Ageinyears單個因素的影響，則incomeaftertheprogram總變差中，不同Ageinyears可解釋的變差為1675.901，抽樣誤差引起的變差為15996.054，它們的方差分別為335.180和20.146，相除所得的F統(tǒng)計量的觀測值為16.637，對應的概率P值近似等于0.如果顯著性水平α為0.05，由于概率P值小于顯著性水平q，則應拒絕原假設,認為不同的Ageinyears對incomeaftertheprogram產生了顯著影響，不同的Ageinyears對incomeaftertheprogram的影響效應不全為0。對比兩張表很容易地發(fā)現(xiàn)：如果從單因素的角度考慮，Levelofeducation對incomeaftertheprogram的影響有更明顯的作用。Withthereason,thediagram,16istheAgeinyearsShanfactormethoddifferenceanalysisresulttoincomeaftertheprogram.Notbadseethat:IfconsideringAgeinyearssinglefactorseffectonly,inbeingthattheincomeaftertheprogramisalwayschangedintodifference,differentAgeinyearsbutinterpretiveunexpectedturnofeventsdispatchesbeing1675.901,theunexpectedturnofeventsthattheerrorsamplingarousesdispatchesbeing15996.054,theirmethoddifferenceis335.180and20.146respectively,isequalto0eachotherexceptthatthegainsFcountingtheamountsobservedvaluebeing16.637,correspondingprobabilityPvaluebeingsimilarwith.Shoulddeclinetheplainhypothesisthen,ifthenotablelevelalphais0.05sinceprobabilityPvalueissmallerthannotablelevelq,theeffectdoesnotsatisfyfor0animpactoftheAgeinyearsthinkingthatdifferentAgeinyearshasproducednotableeffect,diversitytoincomeaftertheprogramoverincomeaftertheprogram.Twoformsdiscoveracontrastveryeasily:IftheanglefromShanfactorthinks,therearemoreobviouseffectintheimpactofLevelofeducationoverincomeaftertheprogram.3．SPSS的相關分析相關分析是分析客觀事物之間關系的數(shù)量分析方法，明確客觀事物之間有怎樣的關系對理解和運用相關分析是極其重要的。Thattherelevanceisanalysedistoanalysethequantityanalysismethodconcerningbetweenobjectivethings,howhavingsomethingtodobetweenobjectivethingsclearanddefinitetotheanalysisunderstandingandwieldingarelevanceisextremelyimportant.函數(shù)關系是指兩事物之間的一種一一對應的關系，即當一個變量x取一定值時，另一個變量y可以根據(jù)確定的函數(shù)取一確定的值。Functionrelationistherelationreferringtoonekindofonetoonecorrespondencebetweentwoobject,istothinkthatanothervariableycantakethevaluethatoneascertainsaccordingtothefunctionascertainingthatwhenavariablextakescertainvalue.另一種普遍存在的關系是統(tǒng)計關系。統(tǒng)計關系是指兩個事物之間的一種非一一對應的關系，，即當一個變量x取一定值時，另一個變量y無法根據(jù)確定的函數(shù)取一確定的值。統(tǒng)計關系可分為線性相關和非線性相關關系。Anotheronekindofcommonexistencerelationistocountrelation.Countingrelationistorefertotwoonekindsoftherelationbeingnotonetoonecorrespondencebetweenobject,thefunctionbeingthatanothervariableyhasnowaytoascertainthatinthelightofwhileavariablextakescertainvalue,takesthevalueonceascertainingthat.Statisticsrelationisdetachableinorderthelinearityisrelatedtononlinearityappearancerelation.事物之間的函數(shù)關系比較容易分析和測度，而事物之間的統(tǒng)計關系卻不像函數(shù)關系那樣直接，但確實普遍存在，并且有的關系強，有的關系弱，程度各有差異。如何測度事物之間的統(tǒng)計關系的強弱是人們關注的問題。相關分析正是一種簡單易行的測度事物之間統(tǒng)計關系的有效工具。繪制散點圖是相關分析最常用的工具。通過散點圖能夠直觀地發(fā)現(xiàn)變量間的統(tǒng)計關系以及他們的強弱程度和數(shù)據(jù)對的可能走向。Thefunctionrelationbetweenobjectiscomparativelyeasytoanalyseandestimate,butbetweenobjectcountrelationbutnotsodirect,butreliableasfunctionrelationcommonexistence,andsomerelationarestrong,somerelationisweak,degreeeveryhasdifference.Howtoestimatestatisticsrelationstrongorweakbetweenobjectistheproblemthatpeopleshowssolicitudefor.Therelevanceanalysestheeffectiveimplementexactlybeingthatestimatingofakindofsimpleandeasytodocountsrelationbetweenobject.Drawingscatteredpointdiagramisthattherelevanceanalysesincommonuseimplement.Thedegreecountingrelationandtheirstrongorweakandthedatamakefortopossibilitybythefactthatscatteredpointdiagramisabletodiscoverthevariableroomvisually.圖表17由圖表17可知：Levelofeducation和incomeaftertheprogram這兩個變量間不存在相關性。表中的相關系數(shù)旁邊的兩個星號（**）表示顯著性水平α為0.01時仍拒絕原假設。一個星號（*）表示顯著性水平α為0.05時仍拒絕原假設。Fromthediagram,17knows:Levelofeducationandtheincomeaftertheprogramcorrelativitydonotexistamongthistwovariables.Twoasterisk(**)ofrelevancemodulusnearbyinformindicatesthatthenotablelevelalphaisthat0.01o'clockstilldeclinestheplainhypothesis.Aasterisk(*)indicatesthatthenotablelevelalphaisthat0.05o'clockstilldeclinestheplainhypothesis.四．Dataanalysis1.SPSS的參數(shù)檢驗—單樣本t檢驗(1)對incomebeforetheprogram變量的t檢驗分析推斷incomebeforetheprogram變量的平均值是否為7元，由于該問題涉及的是單個總體，且要進行總體均值檢驗，同時incomebeforetheprogram的總體可近似認為服從正態(tài)分布，因此，可以采取單樣本t檢驗來進行分析。分析如下：Anddeduceifincomebeforetheprogramvariableaveragevalueare7yuan,sinceowingbeingthatproblemrelatestosinglepopulation,needtocarryoutthepopulationmeanvaluecheckout,simultaneousincomebeforetheprogram'sthestatetotalbutbeingsimilarwithtoregarditbeingpositiveobeyingscatters,canadoptthesinglesamplebooktcheckoutcomingtocarryoutanalysistherefore.Analyticalasfollows:One-SampleStatisticsNMeanStd.DeviationStd.ErrorMeanIncomebeforetheprogram8008.94381.64285.05808圖表11 One-SampleTestTestValue=7tdfSig.(2-tailed)MeanDifference95%ConfidenceIntervaloftheDifferenceLowerUpperIncomebeforetheprogram33.465799.0001.943751.82972.0578圖表12由圖表11可知，800個調查者的incomebeforetheprogram的平均值為8.9438元，標準差為1.64285元，均值標準誤差（s/√n）為0.05808。圖表12中，第二列是t統(tǒng)計量的觀測值為33.465；第三列是自由度為799（即n-1=800-1）；第四列是t統(tǒng)計量觀測值的雙尾概率值；第五列是樣本均值與檢驗值的差，即t統(tǒng)計量的觀測值（33.465）；第六列和第七列是總體均值與原假設值差的95%的置信區(qū)間，為（1.8297，2.0578），由此計算出總體均值的95%的置信區(qū)間為（8.8297，9.0578）元。11knowsthereasondiagram,incomeof800investigatorsbeforetheprogramaveragevalueis8.9438yuan,standarddeviationis1.64285yuan,themeanvaluestandarderror(s/√n)is0.05808.12ishitbyadiagram,secondrowsobservedvaluebeingthattcountsamountsare33.465;Thethirdrowisthatlibertydegree(isn-1=for799800-1);Fourthrowsarethattcountsthetwo-tailprobabilityvaluemeasuringobservedvalue;Fifthrowsarethedifferencethatthesamplebookmeanvalueandthecheckoutareworth,theobservationbeingthattcountsamountsisworth(33.465);Sixthrowsandseventhrowsofbepopulationmeanvalueandoriginalhypothesisisworth95%'sbadconfidenceinterval,is(1.8297,2.0578),95%'sconfidenceintervalcalculatingoutpopulationmeanvalue'sfromthisis(8.8297,9.0578)yuan.該問題應采用雙尾檢驗，因此比較α/2和p/2，也就是比較α和p。如果α給0.05，由于p小于α，因此應拒絕原假設，認為incomebeforetheprogram變量的平均值與7元有顯著差異。95%的置信區(qū)間告訴我們有95%的把握認為incomebeforetheprogram變量的平均值在8.8297~9.0578元之間，7元沒有包含在置信區(qū)間內，也證實了上述推斷。Beproblem'sturntoshouldadoptthetwo-tailcheckout,comparealpha/2withp/2therefore,comparealphawithpthatis.,ifthealphagives0.05becausepissmallerthananalpha,shoulddeclinetheoriginalhypothesistherefore,thinkthatincomebeforetheprogramvariableaveragevaluehasnotabledifferencewith7yuan.95%'sconfidenceintervalinformsusoftheassurancehaving95%thinkingthatincomebeforetheprogramvariableaveragevalueisin8.8297~7yuancontainwithinconfidenceinterval,alsoconfirmabove-mentioneddeductionbetween9.0578yuan.(2)對incomeaftertheprogram變量的t檢驗分析推斷incomeaftertheprogram變量的平均值是否為15元，由于該問題涉及的是單個總體，且要進行總體均值檢驗，同時incomeaftertheprogram的總體可近似認為服從正態(tài)分布，因此，可以采取單樣本t檢驗來進行分析。分析如下：Anddeduceifincomeaftertheprogramvariableaveragevalueare15yuan,sinceowingbeingthatproblemrelatestosinglepopulation,needtocarryoutthepopulationmeanvaluecheckout,cometotalbutsimilarincomeaftertheprogramthinkoftocarryoutanalysisatthesametimeobeyingnormaldistribution,beingabletoadopttheShansamplebooktcheckouttherefore.Analyticalas