[农业]使用回归分析分析人均收入和粮食单价.doc

使用回归分析分析人均收入和粮食单价对人均食品支出的影响 我选用的是曲线估计中的复合模型分别对人均收入和粮食单价对人均食品支出的影响进行复合回归方程拟合。拟合的方程为：y=a*bx ,其中a和b 为下面分析中的表4和表7中的constant和b1 。以下是分析的结果：表1Model DescriptionModel NameMOD_6Dependent Variable1人均食品支出Equation1Compounda,Independent Variable人均收入ConstantIncludedVariable Whose Values Label Observations in PlotsUnspecifieda. The model requires all non-missing values to be positive.表2 Variable Processing SummaryVariablesDependentIndependent人均食品支出人均收入Number of Positive Values3131Number of Zeros00Number of Negative Values00Number of Missing ValuesUser-Missing00System-Missing00表3Case Processing SummaryNTotal Cases31Excluded Casesa0Forecasted Cases0Newly Created Cases0a. Cases with a missing value in any variable are excluded from the analysis.拟合的人均收入对人均食品支出的复合回归模型的检验报告如下表，模型的估计参数为a=294.222,b=1,所以拟合的方程为：y=294.222*1x, 又sig.的值为0，小于0.05,说明拟合程度很好。表4Model Summary and Parameter EstimatesDependent Variable:人均食品支出EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1Compound.794111.967129.000294.2221.000The independent variable is 人均收入. 下图是拟合的该模型的曲线和实际测量值的连线情况。 图1表5Case Processing SummaryNTotal Cases31Excluded Casesa0Forecasted Cases0Newly Created Cases0a. Cases with a missing value in any variable are excluded from the analysis.表6Variable Processing SummaryVariablesDependentIndependent人均食品支出粮食平均单价Number of Positive Values3131Number of Zeros00Number of Negative Values00Number of Missing ValuesUser-Missing00System-Missing00 拟合的粮食单价对人均食品支出的复合回归模型的检验报告如下表，模型的估计参数为a=418.646,b=2.094,所以拟合的方程为：y=418.646*2.094x, 又sig.的值为0，小于0.05,说明拟合程度很好。表7Model Summary and Parameter EstimatesDependent Variable:人均食品支出EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1Compound.50529.599129.000418.6