统计分析与SPSS应用论文Word格式文档下载.doc

1、4072990535.4 2865.52492781847.033115215452.01213.04河 北154.3831589803414710335.9 3268.7992051864.851605120223.09140.97山 西42.2812578911501765254.8 1603.7580712399.131803103492.555.26内蒙古27.7811137751049877413.9 1429.2627004653.961401124381.7670.17辽 宁206.1370111928047109996.8 6123.224178121748.782412146

2、594.95367.55吉 林67.3215993141539718170.8 1545.2534146401.881880125181.5392.62黑龙江134.621407022120957409.4 2260.11028423857.151939126932.75120.3上 海644.121175464716997866672.8 9481.6103491593300.825855335707.331553.95江 苏659.412697793152073782032.5 12316.248935393178.912651190336.59676.6浙 江288.2912952409

3、181392681583.9 13858.948492112794.253108249855.4831.7安 徽193.3535027334137613768.8 4362.316497971429.241782116094.03165.84福 建176.747779416774411632.4 5795.717780611384.832560175423.96318.32江 西174.7424283512586804783.9 3325.28857121168.871325101963.6685.75山 东563.65764786485600421569.1 8283.92797890252

4、5.172045158188.35435.09河 南217.0625882143215054589.6 3940.610093981043.511573113244.37145.58湖 北169.3233728084464587802.3 4055.216460441342.921672122325.95157.96湖 南154.6633486553706899945.6 4071.813357341188.791511139864.17133.04广 东824.6613558422186388542227.2 13911.661674733346.0234822397712.651470.5

5、9广 西95.6919234762392766609.6 2998.9835891820.362083138872.2899.54海 南14.5655991767014241.5 684201173125.762405139420.5623.02重 庆98.4239309195314445863.4 616015471671317.121766135185.41246.99四 川211.0251008036261544258.4 7278.519797842101.9815721358310.33380.13贵 州41.2412166031493706278.0 2443.3599877554

6、.34138595033.0271.84云 南98.1914993052004638380.9 1828.7496494538.111978137891.47103.18西 藏4.753934601664.2 38.4133609.562748190820.041.79陕 西122.4923117192401051369.6 2490.5708387509.361731130482.685.05甘 肃38.04720818799711155.2 1448.1386734261.47175490781.9530.23青 海6.3826239426532093.1 426.717389693.85

7、1583129780.5511.71宁 夏10.0567191268303763.6 941.9397845308.21123900.6641.43新 疆26.9210470011133614263.7 1282.3623047643.371585140601.4107.52 数据来源：中国统计年鉴2005、中国房地产统计年鉴2005三、数据统计处理（一）因子分析用SPSS11软件进行分析，得到特征值、方差贡献率和累积贡献率（表2），可见提取前两个因子，方差贡献率达92.75%85%。因此前两个因子足以反映房地产业的发展水平。表2 特征值及方差贡献率Component Initial Eige

8、nvaluesExtraction Sums of Squared LoadingsTotal% of VarianceCumulative %18.85680.50921.34612.23992.748初始因子载荷矩阵为表3，由表3可以计算两个因子F1、F2的表达式。表达式中的各变量是标准化后的变量，表达式中的系数为因子系数除以相应特征值开平方根后所得到的单位特征向量。表3 因子系数矩阵F1=（0.901zx1+0.972zx2+0.956zx3+0.784zx4+0.951zx5+0.947zx6+0.968zx7+0.76zx8+0.826zx9+0.805zx10+0.962）/Sqr

9、t（8.856）F1=（-0.248zx1-0.06zx2+0.105zx3-0.505zx4-0.213zx5+0.23zx6-0.187zx7+0.632zx8+0.516zx9-0.445zx10+0.147zx11）/Sqrt（1.346）由F1和F2，以及方差贡献率，还可计算因子的总得分值F=0.8051F1+0.1224F2表4给出了各地区房地产业发展水平的因子得分及总得分值表4. 房地产发展水平的因子得分F1F2F 上海 7.2409 3.1355 6.2133 湖 北 -0.3260 -1.0050 -0.3854 新 疆 -2.1280 0.3513 -1.6703 广东 7.6086 -1.5687 5.9336 安 徽 -0.4344 -0.7725 -0.4443 内蒙古 -2.1615 -0.0612 -1.7477 北京 5.0621 2.5569 4.3884 湖 南 -0.5524 -0.8371 -0.5472 山 西 -2.2040 0.0308 -1.7707 浙江 4.8409 0.0852 3.9078 河 南 -0.9026 -0.8274 -0