回归分析例题SPSS求解过程.docx

1、回归分析例题SPSS求解过程回归分析例题SPSS解过程1、一元线性回归W4.2.1为研究家庭收入与家庭食品支出的关系，随机抽取了10个家庭.得到表4.2.1的数据.试根据这些数据：1）建立家庭食品支出对家庭收入的样本回归直线；2）预测当家庭收入为420。元时，家庭的平均食品支出及其置信度为95%的预测区间.表4.2.1惠雇收入与食品支廿般据单位工百元家蜓12345678g1。家庭收入20303340151326383543食品支出7981154810910SPSS解过程:Uirti-tlod-SPSSDataHdn_i:oitFxleEdLtVicwDa.t.Traxsoi-mAxkialyz

2、eGy4KsU1.1Xi.iesWxxxdLowH工p人|Q|昌1回1J_dI由I*J丁fT口用厂|式限10:食品支出1O家庭收入1食品支出1var|var|var|varI120.00兀口口2300O9OO333.0080D440.0011.OD61500S.OO813OO4OO72SDOaon833.001O.ODy3Sno9.OU104300_1a1112pTZTTri1itied-SPSS口足，总。rEileditMiewDataIransf0rm|graphsUtilitiesHiridowHelpUQ吕里|G1=力eeript.iven51ft-tistickTables卜Comp

3、areM.eana4GnexLiliearModl加而i些adMiodais10：备品支出p10家庭收入1食品支出1varvarvar120.0030.0033.0040.0015.0013.0026.003B.0D35.0043.007.009.006.00T1.005.004.006.0010.009.00234RuEre：5，ionLift*-.5LgglLineii-*Rat*Raduetiaxt33-Jffonp-aretricTests.Ti_meSeiriesSuJTVl.v-ll.口fflultiplR后pon与q归Nii3-1nsJalu.erfkjialyi-3.Compi

4、eKSamples.QurireEstima.t.1on.6Bin-ajryLoictic.Mult*1JwiEtig.Orjjiri-aJL-Probit.7891010.00KonJ-inaur.ghtl？Etim4itian.：=SLaEsLuam七Sq.u.4res.1512(007.0323C009.0333:008.0344C.0011.0J51E,005.0JJ1-004,022E008.0J13E0010.0J3E009.03OKHe5elhdepertferJfs!母冢就入SdectaiVdicUe:HelpeLab5l5:ResideWLSWeghi:$!cndc(dcev

5、atcns22LinearRegressionLinearRegression:Statistics|Gjnl泣eCaicdRegressionCce;lcenlSPEstmatesvCcttifercBHen，覆-CovaiiartemalriK17ModelfitrRscwiedchangerQesairfvesrPalcndpailialccfrefetnjFCojlrwiMd叨烟6“Cepjrxfenl：Blcckloll2416V115就比JP&怆.|Save.-Dyibin-Watsonr&附加（1即而什。跳节c而佗（3+RegressionVariablesEnteredjRer

6、novedbModelVariablesEnteredVariablesRemovedMethod1家庭I攵入iEntera.Allrequestedvariablesentered.b.DependentVariable:便品支出ModelSummaryModelRRSquareAdjustedRSquareStd.ErroroftheEstimate1.951a,904892.73304aPredictors:(Constant),家庭收入ANOVAbModelSumofSquaresdfMeanSquareFSig.1Regression40.601140.60175.559.0003R

7、esidual4.2998.537Total44.9009a.Predictors:Constant),家庭收入b.DependentVariable：食品支出CoefficienlsBModelMndardlzedCoefficientsStandardizedCoefficientstSig.95%ConfidenceIntervalforBBSid.ErrorBetaLowerBoundupperBound1位喇2.1737203.017.5123.333家跳人.202023-i：i8.692000,149.266a.DependentVariable判别：？=4十?=2173+0.20

8、2(,且x与y的线性相关系数为R=0.951,回归方程的F检验值为75.559,对应F值的显著性概率是0.0000.05,表示回归方程不具有显著性。每个系数的t检验值分别是3.017与8.692,对应的检验显著性概率分别为：0.017(0.05)和0.000(ClassifxDataReductioil上ScalegenpaarMttrieTtstsTimeSeries量SwrvivilMjjltipleRe印onse卜MissinzValueAnalsiz.Cm-veEstimation.6710.00BinaryLogiitia789.93MultiziomialLogistic.Ordi

9、nal.,.Frobi匕B99.99g-1010.4910111059Nonlinear.iSightEstirnfttin.r.2-StsgeLeaitSquired.-111210EO121310.80131410EOCompleacSamplesOptimalScaling.14151090IU.UUULJ.3Ir151610.761600009292.375B171819AnalyzeFileEditViewDataTraitsformGraphsUtilitiesWindowHelp次数*容积丫126.42238.3034S.5S459.6056970671000739.93899.

10、9991U10.49101110.50111210.601213103013141060141510.9015ie10.7620CurtreEstaationVUV1B管您合DependentMthRsqd.f.容弗只容枳丫QUA.859CUB.921Q印enderM就#Ymiatfe:元TjffleCaseLabels:mModelsLinear*Quadratic一LogarithmicF叁Mg厂lveiseI-PowerF口中国MQVA3*EastsBesetCahcelHelpBIncludeconstantinequatorRPlatrnocfefe广Coflcoiid厂Growth

11、广厂E*ciEntiallLogisticU即rbmnd|Save.FSigfbOb1b2b31236.646092774OB-.02901142.B4411B31.7DEB-.1534.口口4OYObservedQuadkmtic:Cul.dc2所以，二次式为：Y=6.09270.7408x-0.029x2_3三次式为：Y=4.1181.7068x一0.1534x20.0046x32、把Y与X的关系用双曲线拟合:作双曲线变换：ULv次数XI容积YVIuvarvarv126.42.5000.1558238.20,3330.1220349.58.2500.1040459.50.2000.1053

12、569.70.1667.10316710.00.1420.1000789.93.1250.1007899.99.1110.100191010.49.1000,0953_101110.59.0900.0944111210.60.0830.0943121310.80.0760.0926131410.60.0714.0943141510.90.0667.0917151610.76.0625.09261920rQ第叟卜ICompute.llnVisualBander.次数XCount.RankCases.AutomaticRecode.V1U1varvar1_2231.85942.1041_34Cre

13、ateTimeSeriesReplaceMissingRandomNumberSeed.122SA7_45lues.2.2513_562.2721672.302678Kunre2.2956_899.999.0000.10012.301691010.4910,0000.09532.3504101110.5911,0000,09442.3599111210.6012.0000,09432.3609121310.8013.0000.09262.3795131410.6014.0000.09432.3609141510.9015,0000.09172.3888151610.7616.0000.0929

14、2.3758TransformeEditViewRataAnalyzegraphsUtilitiesWincowHelp171819次数XJ容积YCoaputeVariable126.42TargetVariable:NumericExpression238.20M1/次数x3J49.58950Type&LabeL|679701000或容积YLU+II7|8|9|Functions:|789109.939.991049VU磅VI，U1土I山13/业皿ABS(numexpr)aANYJtest,value,value,.)ARSIN(numexpr)ARTAN(numexpr)CDFNORM(z

15、value)COF.BERNOULU(q,p)101110.5911J2121310601080H113I4141510.6010.90IOK|Raste|Reset|Cancel|Help|15161D7K一一一一一14RegressionVariablesEnteredjRemovedbModelVariablesEnteredVariablesRemovedMethod1VaEntera.Allrequestedvariablesentered.b.DependentVariable:UModelSummaryModelRRSquareAdjustedRSquareStd.Errorof

16、theEstimate1.968.938.933.0042568a.Predictors:(Constant),VANOVAbModelSumofSquaresdfMeanSquareFSig.Regression.0041.004196.227.000aResidual.00013.000Total.00414a.Predictors:(Constant),Vb.DependentVariable:Ucoemuients0ModelunslandardizedCoefficientsstandardizedCoefficientst95%ConfidenceIntervalforBBStd.

17、ErrorEstaLow&rBoundUpperBound1(Conalarrt).082.00244,514.000.070086V,131,009,96314.DOB.000,111151a.DependsmOanatueU11判别：U=0.0820.131V,u=-,V=-,V与U的相关系数为R=0.968,回归yx方程系数的F检验值为196.227,对应F值的显著性概率是0.000(0.05),表示线性回归方程具有显著性，每个系数的t检验值分别是440514与14.008,对应的检验显著性概率分别为：0.000(0.05)和0.000(-(-1：.次数X容积Yur1216.42,5000.1558238.20.3333.1220349.5825001044459.5020001053569.701667.10316710.0014291000789.931250,1007899.99.1111.100191010.49.1000.0953101110.590909,094411121060