(整理)SPSS实现一元线性回归分析实例.

1、SPSS实现一元线性回归分析实例2009-12-1415:311、准备原始数据。为研究某一大都市报开设周日版的可行性，获得了34种报纸的平日和周日的发行量信息(以千为单位)。数据如图1所示。SPSS17.0.isav11一S3PSSStatisH|irtseEditorie&Myew3自iranjromArntneOrwhsunitsAdd-on¥»ndcr*卜P员V协醫囲|*H暫曲础缶闇零WHSundaynewpaperwar_.91.952486/50&BahinioreSun.251&9S179629&S&sto-nGIdIje

2、3355.62S235CSBoslcnHerald423855529B.451CharIo14£ObSPrS537.78056909?CtiicgoSunTim73377511332WChicagoTribuner138.33234B.741ChcinmatiEnqu8262.62J4I7.779DarwerPact2O&2OJ3U52?DeMoinesF?egi1023t17?蹈曲HertfordCour?n11449755&2C75?HoustonChronic12268571423305KansasCil/Sis13165.736202.6HLosAngeles

3、D$i划1163801531.52?LasAagelesTinn/豫.'.444.561563.価MismiHeraldISd12.07168575們耐皤pdh士Sl1Z2722WK4-241hl*祥6怜申nyTimISZB1.796363.240NatrYoriiBily图12、判断是否存在线性关系。制作直观散点图：(1)SPSS:菜单Analyze/Regression/linearRegression,如图2所示:精品文档图22）打开对话框如图3图3图3中，Dependent是因变量，Independent是自变量，分别将左栏中的Sunday选入因变量,daily选入自变量，ne

4、wspaper作为标识标签选入caselabels.(3)点击图3对话框中的plots按钮，如图4所示：图4将因变量DEPENTENT选入Y:,自变量ZPRED选入X:continue返回上级对话框。单击主对话框OK.便生成散点图如图5所示：ScatterplotDependentVariable:Sunday2QOO.OOQ-NbwY1500.000-LqsArOAHpunw1000.000-500.000-C.QQO-ChicayoTi血严響啊咖PhiladelphiaIn°hiewsday0NewYorkDaily0QBosi(?nGl口肚PittsburghPresMilin

5、ea|J0liE513°anFranciscocKansasCityStaoPenveiPo&OOChiesgoSunTim出MoinesR期1ford盹間口Q班声蒯冋专SunPj1iainiHeraldPocher摇霊胡严“帥加噌吊裾眇皿怖纲OrleansTimFiance炖%仙血ObSer0rangeCountRLosAngelesDaiOmahaWor|dHerB0Et0nHeialdToT2RegressionStandardizedPredictedValue图5从以上散点图可看出，二者变量之间关系趋势呈线性关系。2、回归方程菜单Analyze/Regression

6、/linearRegression，在图3对话框的右边单击statistics如图6所示：Dependent:StErtistic;.RegressionCGefTicient回Modelfit叵Esftimate'?RchangeIXIPlots.Save.OjationsConfidenceintervalsLevelC%):9LJDea.GriptiuePartandpartialcorrelationsvariancematrixCflllinsaritydiagnostics'ResidualsDurbin-WatsonJCasEwjsEdiagnosticsOutl

7、iersoutsidsstandardtJeviat'oris仁AllcasesContinueCancelHelp图6regressioncoefficient回归系数，estimates估计值，confidenceintervalslevel:95%置信区间，modelfit拟合模型。点击continue返回主对话框，单击OK.结果如图7、图8所示：VariablesEiitered/Removetl1'1ModelEnablesEnteredVariablesRemovediviethcid1daily3Entera. Allrequestedvariablesenter

8、ed.b. DependentVariable:；sundayModelSummaryModelRRSquareAdjustedRSquareStd.ErrorottheEstimate1,95Sa.915.915109.42-1137a. Predators;Constant),dailyb. DependentVariableuriday图7图7中第一个图是变量的输入与输出，从图下的提示可知所有变量均输入与输出，没有遗漏图7中的第二图是模型总和R值，R平方值，R调整后的平方值，及标准误。ANOVAbModelSunnofSquares：dfMeanSauareFSia.1Regreesio

9、rResidualTotal4292652595383135.530467570S.126132'尹429265t59511972.985：i358.5'28.000da. Predictors:Bontant>(dailyb. DependentVariable:SundayC(teffici&irtsaModelUn'standardizedCoefficients-：StandardizedCoefficientsiSig.LcBStd.ErrorBeta1(Constant)daily1318361.340S5.804.071.958.38618.

10、935.702.000a.DependentVariab!e:Sunday图8图8中第一图为方差统计图，包括回归平方和，自由度，方程检验F值及P值。图8第二图为回归参数图，从图中可知，constant为回归方程截距，即13.836，回归系数为1.340,标准误分别为：35.804和0.071，及t检验值和95%的置信区间的最大值和最小值。因此回归方程可表示为：Y=1.34X+13.836。X因变量，即数据表中的daily,Y是因变量，即数据表中的sunday.SPSS实现一元线性回归分析实例2009-12-1415:311、准备原始数据。为研究某一大都市报开设周日版的可行性，获得了34种报纸的

11、平日和周日的发行量信息（以千为单位）。数据如图1所示。SPSS17.0Sunday191.952J36-50&BaltimoreSim51G.9B1S&st:nGbhE355.62S緒的BcslonH忖制23855529B.J51ChaiIolieQtaser537.70056SC9J匚SunTim7337751133249ChicsoTfibune18.33234B744QinG-innaliEnqu262.S2J417779D0fi*erPaet2O&2O43U53?DmMam?5Regi23i!7镒曲HatordCouren449.755&2C75?Hou

12、stonChronic2B857142330&KansasCH/Sis165.7X202阳LowAngelesg11触3801531.527LasAagelesTrnn444.561563.価MiamiHeraldd12.071686如Mi耐陌pel占Sli3241blpw0|甲申nyT|n7fit736963740NwYiiikDbiljfnewpaper图12、判断是否存在线性关系。制作直观散点图：(1)SPSS:菜单Analyze/Regression/linearRegression,如图2所示:图22)打开对话框如图3图3图3中，Dependent是因变量，Independe

13、nt是自变量，分别将左栏中的Sunday选入因变量,daily选入自变量，newspaper作为标识标签选入caselabels.(3)点击图3对话框中的plots按钮，如图4所示:图4将因变量DEPENTENT选入Y:,自变量ZPRED选入X:continue返回上级对话框。单击主对话框OK.便生成散点图如图5所示：ScatterplotDependentVariable:Sunday2QOO.OOQ-NbwY1500.000-LqsArOAHpunw1000.000-500.000-C.QQO-ChicayoTi血严響啊咖PhiladelphiaIn°hiewsday0NewYo

14、rkDaily0QBosi(?nGl口肚PittsburghPresMilinea|J0liE513°anFranciscocKansasCityStaoPenveiPo&OOChiesgoSunTim出MoinesR期1ford盹間口Q班声蒯冋专SunPj1iainiHeraldPocher摇霊胡严“帥加噌吊裾眇皿怖纲OrleansTimFiance炖%仙血ObSer0rangeCountRLosAngelesDaiOmahaWor|dHerB0Et0nHeialdToT2RegressionStandardizedPredictedValue图5从以上散点图可看出，二者变

15、量之间关系趋势呈线性关系。2、回归方程菜单Analyze/Regression/linearRegression，在图3对话框的右边单击statistics如图6所示：Dependent:StErtistic;.RegressionCGefTicient回Modelfit叵Esftimate'?RchangeIXIPlots.Save.OjationsConfidenceintervalsLevelC%):9LJDea.GriptiuePartandpartialcorrelationsvariancematrixCflllinsaritydiagnostics'Residua

16、lsDurbin-WatsonJCasEwjsEdiagnosticsOutliersoutsidsstandardtJeviat'oris仁AllcasesContinueCancelHelp图6regressioncoefficient回归系数，estimates估计值，confidenceintervalslevel:95%置信区间，modelfit拟合模型。点击continue返回主对话框，单击OK.结果如图7、图8所示：VariablesEntered/Removetl1'1Model''-VariablesEnteredVariablesRemove

17、dMethad1daily3Entera. Allrequestedvariablesentered.b. DependentVariable;；sundayModelSummaryModelRRSquareAdjustedRSquareStd.ErrorottheEstimate1,95Sa.915.915109.42-1137a. PredirtorsifConstarit),dailyb. Dependent-Variableuriday图7图7中第一个图是变量的输入与输出，从图下的提示可知所有变量均输入与输出，没有遗漏。图7中的第二图是模型总和R值，R平方值，R调整后的平方值，及标准误

18、。ANOVAbModelSunnofSauares:dfMeanSauareFSia.1RegressiorResidualTotal4292651595383135.5304675788.126132'尹4292654-595119/2.985S58.528.000da. Predittors:/Critant),dailyb. DependentV-ariable:SundayC(teffici&irtsaModelUnstandardizedCoefficients-：StandardizedCoefficientsiSig.LcE8td.ErrorBeta1(&onst