1、pip2i21i10pip2i21i10ixbxbxbbxbxbxbb Yiiiiyyy02bQQi020202110111011100pipipiipipipiipipiixxbxbbybQxxbxbbybQxbxbbybQ0202021piiiiixx0001piiiiixx（最小二乘法）0002211112211121pnnppnnnxxxxxx000111212111211npnppnxxxxxx0exeXXBXYXeXBYYXXXBYXXBX1矩阵表示)555.5()232.7()326.8(2207.11544.0546.1353tValuexxyC Co oe ef ff fi
2、ic ci ie en nt ts sa a-1353.546162.576-8.326.001.544.075.5777.232.0021.207.217.4435.555.005(Constant)X1X2Model1BStd.ErrorUnstandardizedCoefficientsBetaStandardizedCoefficientstSig.Dependent Variable:Ya.CoefficientsCoefficientsa a.4882.218.220.829.576.136.8034.245.0014.7691.983.4702.404.029-2.1451.01
3、6-.416-2.111.051(Constant)x1x2x3Model1BStd.ErrorUnstandardizedCoefficientsBetaStandardizedCoefficientstSig.Dependent Variable:ya.C Co oe ef ff fi ic ci ie en nt ts sa a-13534.15138.920-2.634.039.209.0631.8043.292.017-.060.144-.149-.416.692.763.326.9132.341.058.141.0521.0622.703.035-.855.292-2.644-2.
4、932.026.227.088.1822.595.041(Constant)x1x2x3x4x5x6Model1BStd.ErrorUnstandardizedCoefficientsBetaStandardizedCoefficientstSig.Dependent Variable:ya.ESSRSSTSSyyyyyyxebxebebxbxbbeyeyeyyeyyyyyyyyyyyyyyyyyyyyiiiiipiipiiipipiiiiiiiiiiiiiiiiiiiiiii22211011022202yyyyyA AN NO OV VA Ab b803.8163267.93920.939.
5、000a204.7341612.7961008.55019RegressionResidualTotalModel1Sum ofSquaresdfMean SquareFSig.Predictors:(Constant),x3,x1,x2a.Dependent Variable:yb.ibisbt 22iiybxxssi12pnRSSabFiiii22yyyyTSSESSRiiTSSRSSpnnRTSSRSSTSSESSR111122pppppprrrrrrrrr212222111211yyypyypyppppypyprrrrrrrrrrrrrrrr2121222221111211yyiiiypiiyijjiiijpjjiiijrr 1112.111112.000bxby,020200yyStySty返回22yyyyTSSESSRii),1(2dfFdfRSSQFabQiiiii)1,1(1)(lnFlnRSSQFllk剔直到 F引 F引 且 F踢 F踢则逐步回归结束The End
