管理统计作业.doc

管理统计作业题目：对某公司81名员工工资进行分析，分析其任职部门、性别、年龄与工资间的关系。序号姓名单位性别年龄工资1陈子元002520002李应杰002727503刘恩利202822504马韧203027505马建军003131586艾丽013132007李荣华103131008陆玉刚003237509任立玲0131312510许志强1031367811卞玉杰0132400012董小凤0132400013韩帅臣1033325014王庆平1033334515于铁华1033354316崔永善1033321317郑顺0034525018檀凤志2034450019李春华0034534320王玉才2034443521王福全0034458022耿俊山2034465323高书臣0035525024甘树才2035455025段玉茹0135375026张富荣2135303527董淑花0135375028刘国英2136302529王幸荣0136375030刘桂娟2136332231周丽荣0137450032高宝良2037525033张月萍2137477534刘廷祥1037466035陈金凤0138450036郭世友2038525037王淑芬2138477538孙建平1038450039高荣英0138450040曹彦贵2038525041刘子荣2138434042陈俊杰1038458043裴丽艳0139450044程相波2039552045徐丽芹2139477546吴桂杰1039450047李恩霞2139537548裴志军1039480049弭会兰2140537550吴东顺1040480051孙志霞2140537552刘作贵1040480053史秋芳2141537554刘占国1041490055韩双菊2142525056王琳2142534057张月霞2143549058张锦绣1143337059王玉霞1144345060王慧梅1144325061杜秀君1145298062孙玉霞1145286063毕凤芝1145300064赵洪玲1146453065宋志梅1146423566唐雅君1146452567崔淑菊1147425068牛瑞英1147397069张淑媛1147426570董艳敏1147452571吴晓景1148468072王秀芹1148478073张春艳1148492074郑英欣1148509075刘春梅1148462076陈静1149433077张翠英1149452578董健颖1149564079刘金玲1149496080朱文革1150492081曹淑华11504480一、 绘制散点图及箱形图：二、 进行相关分析：Correlations 年龄工资年龄Pearson Correlation1。435（*）Sig。 (2tailed).。000N8181工资Pearson Correlation.435(*)1Sig。 （2tailed)。000.N8181 Correlation is significant at the 0。01 level (2tailed）。Correlations 年龄工资Kendalls tau_b年龄Correlation Coefficient1.000.323(*)Sig. （2tailed）.000N8181工资Correlation Coefficient.323（*）1。000Sig。 （2-tailed)。000.N8181Spearmans rho年龄Correlation Coefficient1.000。422(*）Sig. （2tailed).。000N8181工资Correlation Coefficient。422(）1.000Sig. (2tailed)。000.N8181* Correlation is significant at the 0.01 level (2tailed).三、进行回归分析：Model Summary(b)ModelRR SquareAdjusted R SquareStd。 Error of the Estimate1。435（a）.189.179782。083a Predictors: （Constant）, 年龄b Dependent Variable： 工资ANOVA(b)Model Sum of SquaresdfMean SquareFSig。1Regression11268013.041111268013.04118.422。000（a)Residual48320664.09479611653.976 Total59588677。13680 a Predictors: （Constant）, 年龄b Dependent Variable: 工资Coefficients（a）Model Unstandardized CoefficientsStandardized CoefficientstSig。BStd. ErrorBeta1（Constant)1912.786555.021 3.446.001年龄60。25314。038.4354.292.000a Dependent Variable： 工资四、进行方差分析（只考虑因子主效应）： 第一种Tests of BetweenSubjects EffectsDependent Variable: 工资 SourceType III Sum of SquaresdfMean SquareFSig.Corrected Model4415182。358（a）31471727.4532.054.113Intercept1296671423。33811296671423。3381809。632.000性别305238。5491305238。549。426。516单位4131898.93422065949.4672.883。062Error55173494.77877716538。893 Total1533423433.00081 Corrected Total59588677。13680 a R Squared = 。074 (Adjusted R Squared = .038）Parameter EstimatesDependent Variable: 工资 ParameterBStd。 ErrortSig。95 Confidence IntervalLower BoundUpper BoundIntercept4637.182190。52324.339。0004257.8025016.562性别=0125。737192。647.653.516509.346257。873性别=10（a）.。单位=0-602。345259。9412.317.023-1119.95384.738单位=1-384。963220。904-1.743。085-824.83954.912单位=20(a)。.a This parameter is set to zero because it is redundant。Tests of BetweenSubjects EffectsDependent Variable: 工资 SourceType III Sum of SquaresdfMean SquareFSig.Model1478249938。222（a)4369562484。556515.761。000性别305238。5491305238。549。426。516单位4131898.93422065949.4672.883.062Error55173494。77877716538。893 Total1533423433。00081 a R Squared = .964 (Adjusted R Squared = 。962)Parameter EstimatesDependent Variable： 工资 ParameterBStd. ErrortSig。95% Confidence IntervalLower BoundUpper Bound性别=04511。445206.11821。888.0004101.0134921。878性别=14637.182190。52324。339。0004257。8025016。562单位=0602.345259。941-2.317。023-1119。953-84.738单位=1-384.963220。904-1。743。085-824.83954.912单位=20(a).。a This parameter is set to zero because it is redundant。5