数据的回归分析.doc

数据分析方法 实验报告专业班级姓名组别同组实验人员信息与计算科学01实验日期2014-11-14周五5-8节 指导老师刘劲光 评分实验名称数据的回归分析实验目的熟悉变量间的回归模型并对变量进行预测实验步骤：实验步骤：一、 用Excel软件编写实验数据，并保存二、 安装SPSS并导入Excel保存的数据三、 按照题目要求，计算相应的数据，和绘制相应的图形四、 运行结果如下：Total Variance ExplainedComponentInitial EigenvaluesExtraction Sums of Squared LoadingsTotal% of VarianceCumulative %Total% of VarianceCumulative %12.42180.68780.6872.42180.68780.6872.53417.80998.4963.0451.504100.000Extraction Method: Principal Component Analysis.Component MatrixaComponent1x1.775x2.943x3.964Extraction Method: Principal Component Analysis.a. 1 components extracted.Total Variance ExplainedComponentInitial EigenvaluesaExtraction Sums of Squared LoadingsTotal% of VarianceCumulative %Total% of VarianceCumulative %Raw1110.00480.35680.356110.00480.35680.356225.32418.49998.85531.5681.145100.000Rescaled1110.00480.35680.3562.40680.20480.204225.32418.49998.85531.5681.145100.000Extraction Method: Principal Component Analysis.a. When analyzing a covariance matrix, the initial eigenvalues are the same across the raw and rescaled solution.CommunalitiesRawRescaledInitialExtractionInitialExtractionx151.74551.7451.0001.000x223.45623.4561.0001.000x361.69661.6961.0001.000Extraction Method: Principal Component Analysis.Component MatrixaRawRescaledComponentComponent123123x15.865-4.165.060.815-.579.008x24.4191.6781.056.912.347.218x37.4892.272-.670.953.289-.085Extraction Method: Principal Component Analysis.a. 3 components extracted.Total Variance ExplainedComponentInitial EigenvaluesaExtraction Sums of Squared LoadingsTotal% of VarianceCumulative %Total% of VarianceCumulative %Raw1110.00480.35680.356110.00480.35680.356225.32418.49998.85525.32418.49998.85531.5681.145100.0001.5681.145100.000Rescaled1110.00480.35680.3562.40680.20480.204225.32418.49998.855.53917.96698.17031.5681.145100.000.0551.830100.000Extraction Method: Principal Component Analysis.a. When analyzing a covariance matrix, the initial eigenvalues are the same across the raw and rescaled solution.Component MatrixaRawRescaledComponentComponent123123x15.865-4.165.060.815-.579.008x24.4191.6781.056.912.347.218x37.4892.272-.670.953.289-.085Extraction Method: P