【正文】 專業(yè)資料整理分享 第二章 簡(jiǎn)單線性回歸模型（1） ①首先分析人均壽命與人均GDP的數(shù)量關(guān)系，用Eviews分析：Dependent Variable: YMethod: Least SquaresDate: 12/23/15 Time: 14:37Sample: 1 22Included observations: 22VariableCoefficientStd. ErrortStatisticProb.CX1RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)有上可知，關(guān)系式為y=+②關(guān)于人均壽命與成人識(shí)字率的關(guān)系，用Eviews分析如下：Dependent Variable: YMethod: Least SquaresDate: 12/23/15 Time: 15:01Sample: 1 22Included observations: 22VariableCoefficientStd. ErrortStatisticProb.CX2RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)由上可知，關(guān)系式為y=+③關(guān)于人均壽命與一歲兒童疫苗接種率的關(guān)系，用Eviews分析如下：Dependent Variable: YMethod: Least SquaresDate: 12/23/14 Time: 15:20Sample: 1 22Included observations: 22VariableCoefficientStd. ErrortStatisticProb.CX3RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)由上可知，關(guān)系式為y=+（2）①關(guān)于人均壽命與人均GDP模型，由上可知，說明所建模型整體上對(duì)樣本數(shù)據(jù)擬合較好。 對(duì)于回歸系數(shù)的t檢驗(yàn)：t（β1）=(20)=，對(duì)斜率系數(shù)的顯著性檢驗(yàn)表明，人均GDP對(duì)人均壽命有顯著影響。②關(guān)于人均壽命與成人識(shí)字率模型，由上可知，說明所建模型整體上對(duì)樣本數(shù)據(jù)擬合較好。對(duì)于回歸系數(shù)的t檢驗(yàn)：t（β2）=(20)=，對(duì)斜率系數(shù)的顯著性檢驗(yàn)表明，成人識(shí)字率對(duì)人均壽命有顯著影響。③關(guān)于人均壽命與一歲兒童疫苗的模型，由上可知，說明所建模型整體上對(duì)樣本數(shù)據(jù)擬合較好。 對(duì)于回歸系數(shù)的t檢驗(yàn)：t（β3）=(20)=，對(duì)斜率系數(shù)的顯著性檢驗(yàn)表明，一歲兒童疫苗接種率對(duì)人均壽命有顯著影響。（1）①對(duì)于浙江省預(yù)算收入與全省生產(chǎn)總值的模型，用Eviews分析結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 12/23/15 Time: 17:46Sample (adjusted): 1 33Included observations: 33 after adjustmentsVariableCoefficientStd. ErrortStatisticProb.XCRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)②由上可知，模型的參數(shù)：，截距為—③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)?zāi)Ｐ偷娘@著性：1），說明所建模型整體上對(duì)樣本數(shù)據(jù)擬合較好。2）對(duì)于回歸系數(shù)的t檢驗(yàn)：t（β2）=(31)=，對(duì)斜率系數(shù)的顯著性檢驗(yàn)表明，全省生產(chǎn)總值對(duì)財(cái)政預(yù)算總收入有顯著影響。④用規(guī)范形式寫出檢驗(yàn)結(jié)果如下：Y=— () ()t= () （）R2= F= n=33⑤經(jīng)濟(jì)意義是：全省生產(chǎn)總值每增加1億元。（2）當(dāng)x=32000時(shí)，①進(jìn)行點(diǎn)預(yù)測(cè)，由上可知Y=—，代入可得：Y= Y=*32000—=②進(jìn)行區(qū)間預(yù)測(cè)：先由Eviews分析：XYMeanMedianMaximumMinimumStd. Dev.SkewnessKurtosisJarqueBeraProbabilitySumSum Sq. Dev.+0958407195Observations3333由上表可知，∑x2=∑（Xi—X）2=δ2x(n—1)= x (33—1)=(Xf—X)2=(32000—)2=當(dāng)Xf=32000時(shí)，將相關(guān)數(shù)據(jù)代入計(jì)算得到：—√1/33+≤Yf≤+√1/33+即Yf的置信區(qū)間為（—, +）(3) 對(duì)于浙江省預(yù)算收入對(duì)數(shù)與全省生產(chǎn)總值對(duì)數(shù)的模型，由Eviews分析結(jié)果如下：Dependent Variable: LNYMethod: Least SquaresDate: 12/23/15 Time: 18:04Sample (adjusted): 1 33Included observations: 33 after adjustmentsVariableCoefficientStd. ErrortStatisticProb.LNXCRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)①模型方程為：lnY=②由上可知，模型的參數(shù)：，③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)其顯著性：1），說明所建模型整體上對(duì)樣本數(shù)據(jù)擬合較好。2）對(duì)于回歸系數(shù)的t檢驗(yàn)：t（β2）=(31)=，對(duì)斜率系數(shù)的顯著性檢驗(yàn)表明，全省生產(chǎn)總值對(duì)財(cái)政預(yù)算總收入有顯著影響。④經(jīng)濟(jì)意義：全省生產(chǎn)總值每增長(zhǎng)1%，%（1）對(duì)建筑面積與建造單位成本模型，用Eviews分析結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 12/23/15 Time: 20:11Sample: 1 12Included observations: 12VariableCoefficientStd. ErrortStatisticProb.XCRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)由上可得：建筑面積與建造成本的回歸方程為：Y=（2）經(jīng)濟(jì)意義：建筑面積每增加1萬平方米。（3）①首先進(jìn)行點(diǎn)預(yù)測(cè)，由Y=，當(dāng)x=，y=②再進(jìn)行區(qū)間估計(jì)：用Eviews分析：YXMeanMedianMaximumMinimumStd. Dev.SkewnessKurtosisJarqueBeraProbabilitySumSum Sq. Dev.Observations1212由上表可知，∑x2=∑（Xi—X）2=δ2x(n—1)= x (12—1)=(Xf—X)2=(—)2=當(dāng)Xf=，將相關(guān)數(shù)據(jù)代入計(jì)算得到：—√1/12+≤Yf≤+√1/12+即Yf的置信區(qū)間為（—, +）（1）①對(duì)百戶擁有家用汽車量計(jì)量經(jīng)濟(jì)模型，用Eviews分析結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 12/23/15 Time: 20:59Sample: 1 31Included observations: 31VariableCoefficientStd. Error