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惠悦等级职位公司月工资市场年工资1Receptionist1500364722Driver1500444352Administrativeassistant2700494003SkilledProductionOperator2500307713StoreKeeper2300292184Foreman4500584705PersonnelAssistant3500500806SecretarytoDirector3900546787SystemsAnalyst60001165708ExecutiveSecretary6500914609EngineeringSupervisor6400820709AccountingSupervisor6100916559PurchasingSupervisor59007265110DistrictSalesManager1100018330510QualityControlSupervisor1000016039811ChiefAccountant1000012527011HROfficer900010289412EngineeringManager1250016637412SalesAdministrationManager1000012433912PurchasingManager980016866613GroupProductManager12000n.a.14FinanceDirector1500020865014HRDirector1480021304514SalesDirector16000386330公司月工资的平均数市场年工资的平均数2100469182400299956133821251050013221395001140821076715312615267269342惠悦等级公司月工资的平均数市场年工资的平均数推算出的市场月工资的平均数C/1332500254311956.23441412.8753185.61545168.666673474.5162500462223555.54700.0082732.35294154348.54180.6592287.572427.666675571.36105138.88888972825.6255601.97113875778695989.92126964.285714144808.511139.1213750019995215380.92148750200703.333315438.72150.0016125000.00170.0018137500.00市场月工资的自然对数EXPONENTIAL惠悦等级Ln(D)7.578774824SUMMARYOUTPUT18.06639774428.153209553RegressionStatistics38.176261797MultipleR0.9261898914#NUM!RSquare0.8578277140.92618989158.338222936AdjustedRSquare0.84490296168.625394284StandardError0.25009357778.630873807Observations1388.69783384999.318218101ANOVA109.640883259dfSS119.644633786Regression14.15128821712#NUM!Residual110.68801476813#NUM!Total124.83930298514#NUM!#NUM!CoefficientsStandardErrorIntercept7.6880194790.144505512XVariable10.1459351180.017913107回归模型E=7.688019479+0.145935118x(x=1,2,---,13)相关系数#NUM!公司月工资的平均数推算出的市场月工资的平均数回归所得的市场数据回归模型斜率检验EXP((G20*I3)+G19)(L2/L1)-115002805.5425250.1571211121003609.0829220.1571211124002307.3133810.1571211145004497.6939120.1571211135003852.3145260.1571211139004206.0052380.1571211160008966.9260610.1571211165007035.3870130.1571211161336317.3181150.157121111050013219.3893900.1571211195008775.54108650.157121111076711778.95125720.1571211112000n.a.145480.157121111526718575.3116833-1最小值中位值最大值纵向比较横向比较同列相比同行相比196922642560n.a.0.32166249128150.10.32382274030970.10.32625315136760.150.43019362342270.150.43472416748610.150.44167500058330.20.45000600070000.20.46000750090000.250.575009375112500.20.5882411250136760.20.551058813500164120.20.551246216200199380.20.61495419440239260.20.6等级越高，往上跃进的可能性就越少，因此高等级需要带宽变大，以利于工资的浮动比较A比较B比较CO/JO/KO/L1.5094495690.807037360.8967401481.185996090.6900910790.8524727051.1415212371.1873799830.8103905180.7001330250.7004922520.8054032451.0351966870.9405241470.8004466631.0683760680.990648280.7955205860.8333333330.5576048730.8249998160.9230769230.8528318390.8555714451.2228925491.1872146120.9242457830.8928571430.7091858110.9984324191.1842105261.2819726161.0354308581.2538311511.1461124691.073800331.35n.a.1.1135916421.2733346431.0465504821.154857482比较的平均表现1.11244350.93058810.9244217三组数都接近1是最好的，但若无法同时满足，则应使设计值与市场值更接近。否则，这种设计没有意义。等级越高，往上跃进的可能性就越少，因此高等级需要带宽变大，以利于工资的浮动三组数都接近1是最好的，但若无法同时满足，则应使设计值与市场值更接近。否则，这种设计没有意义。SUMMARYOUTPUT回归统计MultipleR0.92619RSquare0.857828AdjustedRSquare0.844903标准误差0.250094观测值13方差分析dfSSMSFSignificanceF回归分析14.1512854.15128566.370845.49E-06残差110.6880150.062547总计124.8393Coefficients标准误差tStatP-valueLower95%Upper95%下限95.0%上限95.0%Intercept7.688020.14450653.202251.27E-147.3699658.0060747.3699658.006074XVariable10.1459350.0179138.146835.49E-060.1065090.1853620.1065090.185362RESIDUALOUTPUTPROBABILITYOUTPUT观测值预测Y残差标准残差百分比排位Y17.8339550.1053960.4401653.8461547.74383727.979890.2113170.88252511.538467.93935138.125825-0.38199-1.595319.230778.19120748.271760.139560.58284326.923088.25642858.417695-0.16127-0.673534.615388.34426768.56363-0.21936-0.9161242.307698.4113278.7095650.3917331.635993508.75104888.85550.0032070.01339557.692318.85870899.001435-0.25039-1.0456965.384629.079723109.147370.3420691.42858473.076929.101298119.293305-0.21358-0.8919880.769239.374067129.43924-0.06517-0.2721888.461549.48944139.7311110.0984780.41127496.153859.829589上限95.0%-0.6-0.4-0.200.20.40.605101520残差XVariable1XVariable1ResidualPlot05101505101520YXVariable1XVariable1LineFitPlotY预测Y051015020406080100120YSamplePercentileNormalProbabilityPlot