统计学实验报告(4)

SUMMARY OUTPUT回归统计Multiple R0.941214R Square0.885883Adjusted R 0.878275标准误差38.54168观测值17方差分析df回归分析残差总计SSMSFSignificance F1172972.9172972.9116.44391.82E-081522281.911485.46116195254.8Coefficients标准误差t StatP-valueLower 95%Upper 95%下限 95.0%上限 95.0%Intercept-125.15622.58047-5.542685.64E-05-173.285-77.0272-173.285-77.0272X Variable 1.4030220.13001910.790921.82E-081.1258941.6801511.1258941.680151 ①由回归统计中的R=0.885883看出，所建立的回归模型对样本观测值的拟合程度较好； ②估计出的样本回归函数为：?=-125.156+1.403022 x3，说明公路里程每增加1万公里，轿车生产量增加1.403022万辆； ③由上表中a和β ?的p值分别是5.64E-05和1.82E-08，显然a和β?的p值均远小于显著性水平α=0.05，拒绝原假设α=0、β=0，但由于β对两者的影响更为显著，所以可以说明公 路里程对轿车生产量有显著影响。

（4）轿车生产量与国内生产总值GDP的关系

SUMMARY OUTPUT回归统计Multiple R0.939995R Square0.88359Adjusted R 0.87583标准误差38.92691观测值17方差分析df回归分析残差总计SSMSFSignificance F1172525.2172525.2113.85522.11E-081522729.561515.30416195254.8Coefficients标准误差t StatP-valueLower 95%Upper 95%下限 95.0%上限 95.0%Intercept-70.712718.30702-3.86260.001534-109.733-31.6922-109.733-31.6922X Variable 0.0018290.00017110.670292.11E-080.0014640.0021940.0014640.002194 ①由回归统计中的R=0.88359看出，所建立的回归模型对样本观测值的拟合程度较好； ②估计出的样本回归函数为：?=-70.7127+0.001829x4，说明GDP每增加1亿元，轿车生产量增加18.29辆； ③由上表中a和β?的p值分别是0.001534和2.11E-08，显然a和β ?的p值均小于显著性水平α=0.05，拒绝原假设α=0、β=0，但由于β对两者的影响更为显著，所以可以说明GDP 对轿车生产量有较显著影响。

（5）轿车生产量与城镇居民人均可支配收入的关系

SUMMARY OUTPUT回归统计Multiple R0.917695R Square0.842164Adjusted R 0.831641标准误差45.32719观测值17方差分析df回归分析残差总计SSMSFSignificance F1164436.5164436.580.035112.12E-071530818.312054.55416195254.8Coefficients标准误差t StatP-valueLower 95%Upper 95%下限 95.0%上限 95.0%Intercept-92.905423.8703-3.892090.001444-143.784-42.0271-143.784-42.0271X Variable 0.0329280.0036818.9462342.12E-070.0250830.0407740.0250830.040774 ①由回归统计中的R=0.842164看出，所建立的回归模型对样本观测值的拟合程度较好； ②估计出的样本回归函数为：?=-92.9054+0.032928x5，说明城镇居民人均可支配收入每增加1元，轿车生产量增加329.28辆； ③由上表中a和β?的p值分别是0.001444和2.12E-07，显然a和β ?的p值均小于显著性水平α=0.05，拒绝原假设α=0、β=0，但由于β对两者的影响更为显著，所以可以说明城镇 居民人均可支配收入对轿车生产量有显著影响。

第八章 5.(1)

年份2005季度一二三四一二三四一二三四一二三四鲜蛋销售量四次移动平均13.113.97.910.58758.61010.89.92511.510.459.711.2251112.4514.613.987517.515.6751617.0518.217.837518.418.26252018.3516.918移正平均逐期增长20062007200810.293759.9625-0.3312510.18750.22510.83750.6511.8375113.218751.3812514.831251.612516.36251.5312517.443751.0812518.050.6062518.306250.25625 （2）

年份季度一二三四一二三四一二三四一二三四2005200620072008指数平滑指数鲜蛋销售量α=0.1α=0.3α=0.713.113.913.113.113.17.913.1813.3413.668.612.65211.7089.62810.812.246810.77568.908411.512.1021210.7829210.232529.712.0419110.9980411.119761111.8077210.6086310.1259314.611.7269510.7260410.7377817.512.0142511.8882313.441331612.5628313.5717616.282418.212.9065414.3002316.0847218.413.4358915.4701617.565422013.932316.3491118.1496216.914.5390717.4443819.444891814.7751617.2810717.66347

（3）

年份2005季度12345678910111213141516鲜蛋销售量13.113.97.98.610.811.59.71114.617.51618.218.42016.918SUMMARY OUTPUT回归统计Multiple R0.786703R Square0.618902Adjusted R 0.591681标准误差2.474359观测值16方差分析df回归分析残差总计SSMSFSignificance F1139.2139.222.735980.00031485.714376.12245515224.9144200620072008Coefficients标准误差t StatP-valueLower 95%Upper 95%下限 95.0%上限 95.0%Intercept8.69251.2975656.6990861.01E-055.909511.47555.909511.4755X Variable 0.6398530.1341914.7682260.00030.3520420.9276640.3520420.927664RESIDUAL OUTPUT观测值12345678910111213141516预测 Y9.3323539.97220610.6120611.2519111.8917612.5316213.1714713.8113214.4511815.0910315.7308816.3707417.0105917.6504418.2902918.93015残差3.7676473.927794-2.71206-2.65191-1.09176-1.03162-3.47147-2.811320.1488242.4089710.2691181.8292651.3894122.349559-1.39029-0.93015

（4）

2009年趋势预期值用季节指数调整第一季度第二季度第三季度第四季度19.870720.537121.203521.869921.0087623.2240918.0645720.60261