[農(nóng)業(yè)]使用回歸分析分析人均收入和糧食單價(jià)

1、.使用回歸分析分析人均收入和糧食單價(jià)對人均食品支出的影響 我選用的是曲線估計(jì)中的復(fù)合模型分別對人均收入和糧食單價(jià)對人均食品支出的影響進(jìn)行復(fù)合回歸方程擬合。擬合的方程為：y=a*bx ,其中a和b 為下面分析中的表4和表7中的constant和b1 。以下是分析的結(jié)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 Plot

2、sUnspecifieda. 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

3、Cases31Excluded Casesa0Forecasted Cases0Newly Created Cases0a. Cases with a missing value in any variable are excluded from the analysis.擬合的人均收入對人均食品支出的復(fù)合回歸模型的檢驗(yàn)報(bào)告如下表，模型的估計(jì)參數(shù)為a=294.222,b=1,所以擬合的方程為：y=294.222*1x, 又sig.的值為0，小于0.05,說明擬合程度很好。表4Model Summary and Parameter EstimatesDependent Variable:人均食品

4、支出EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1Compound.794111.967129.000294.2221.000The independent variable is 人均收入. 下圖是擬合的該模型的曲線和實(shí)際測量值的連線情況。 圖1表5Case Processing SummaryNTotal Cases31Excluded Casesa0Forecasted Cases0Newly Created Cases0a. Cases with a missing value in any v

5、ariable are excluded from the analysis.表6Variable Processing SummaryVariablesDependentIndependent人均食品支出糧食平均單價(jià)Number of Positive Values3131Number of Zeros00Number of Negative Values00Number of Missing ValuesUser-Missing00System-Missing00 擬合的糧食單價(jià)對人均食品支出的復(fù)合回歸模型的檢驗(yàn)報(bào)告如下表，模型的估計(jì)參數(shù)為a=418.646,b=2.094,所以擬合的方程為：y=418.646*2.094x, 又sig.的值為0，小于0.05,說明擬合程度很好。表7Model Summary and Parameter EstimatesDependent Variable:人均食品支出EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1Compound.50529.599129.000418.64