最新实验六因子分析分析解析

1、实验六 因子分析一、实验目的学习利用SPSS进行因子分析。二、实验步骤下表资料为25名健康人的7项生化检验结果，7项生化检验指标依次命名为 X1至X7,请对该资料进行因子分析。X1X2X3X4X5X6X73.763.660.545.289.7713.744.78 一8.594.991.3410.027.5010.162.136.226.144.529.842.172.731.097.577.287.0712.661.792.100.829.037.082.5911.764.546.221.285.513.981.306.925.337.302.403.270.620.443.367.638.8

2、48.398.747.003.3111.683.534.761.129.649.491.0313.5713.1318.522.359.731.331.009.879.8711.063.708.592.981.179.177.859.912.627.125.493.689.722.643.431.194.693.012.175.982.763.552.015.511.341.275.814.575.383.431.661.611.572.801.782.093.725.905.761.558.845.407.501.979.849.271.5113.609.0212.671.758.394.92

3、2.5410.053.965.241.434.944.381.036.686.499.062.817.232.301.777.794.395.372.279.467.311.0412.0011.5816.182.429.555.354.2511.742.773.511.054.944.524.508.071.792.101.298.213.082.429.103.754.661.729.416.445.1112.502.453.100.91实验步骤:1.建立数据文件。定义变量名：分别为XI、X2、X3、X4、X5、X6、X7,按顺序输入相应数值， 建立数据文件。2 .选择菜单Analyze一D

4、ata Reduction 一Factor ，弹出“Factor Analysis”对话框。在对话框左侧的变量列表中选变量X1至X7，进入“Variables 框，如图1。单击Descriptives ”按钮，弹出“Factor Analysis: Descriptives” 对话框，在“Statistics ”中选“Univariate descriptives ”项，输出各变量 精品文档的均数与标准差，“在Correlation Matrix”栏内选“Coefficients”，计算相 关系数矩阵，并选KMO and Bartletts test of sphericity ”项，对相关系

5、 数矩阵进行统计学检验，如图2。图1图2单击“Extraction按钮，弹出“Factor Analysis: Extraction对 话框，选用“Principal components方法提取因子，如图3。图3单击Rotation按钮，弹出“Factor Analysis: Rotation” 对话框， 在“Method栏中选择Varimax”进行因子正交旋转，如图4。单击Scores按钮，弹出“Factor Analysis: Scores对话框，选 择“Regression”项估计因子得分系数，如图5。单击“ OK ”钮，得到输出结果。三、实验习题对2008年重庆市40个区县经济发展基

6、本情况进行分析，选择合适的分析变 量，找出影响地区社会经济发展水平的主要因子，并对各地区发展水平进行综合 评价或者对各地区经济发展状况进行分类。选取重庆市40个区市县经济发展基本情况的八项指标进行分析，分别为：X1 工业总产值（万兀），X2 农业总产值（万兀），X3 建筑业总产值（万兀）， X4-地方财政预算内收入（亿元），X5-非农业人口（万人），X6-公路货运 量（万吨），X7-城镇化率（），X8-农村居民人均住房面积（平方米），数据如下：区县工业总产 值（万元）农业总 产值（万 元）建筑业总 产值（万 元）地方财政预算内收入（亿元）非农业人口（万人）公路货运 量（万吨）城镇化率农村居民人

7、均住房面积（平方米）渝中区2242330115037521433959.569341000.00大渡口区3125659240502746787809918.39232710046.95江北区29962473836863491629694545.91182910032.06沙坪坝区4624569619229013482570065805九龙坡区666596790486148893913123358.87131310040.11南岸区38990825086068050417525447.63243710048.16北碚区26515871189693484681060683

8、0.86125471.2441.26渝北区6051440240448158546223362144.07220166.4442.32巴南区351251734531378967812022928.88125169.3939.23万盛区32961862386315683336113.23231770.8145.79双桥区82466544425263262412.8220592.8333.85涪陵区308584937531391268223539633.0485453.9136.07精品文档长寿区155345128244650742717279021.46121048.739.41江津区235458

9、656704851258618835940.02121253.838.53合川区88123247009229372117138532.04140050.838.33永川区136723736644966020814216729.72284454.636.91南川区8866442784591532846797411.7135144.937.56綦江县8622653236219669410249822.18290537.4135.51潼南县2379763193984490833830411.9936228.730.81铜梁县72332926459317414012351614.9529636.413

10、9.98大足县6914312957001745268137417.72102034.3435.51荣昌县119565531075815116210588318.5125736.4132.83璧山县157187915499213806213522715.9285937.9242.00万州区173825742457196609614739951.06172051.0237.55梁平县438658254423925034016611.8165031.743.14城口县157206547966520142662.9510120.3930.52丰都县235975216427951393686315.05

11、12528.5135.04垫江县5290922625971621915247914.43112330.635.90忠县2775962760322081154148616.0120328.937.17开县4208193874862926894822621.29642.63240.84云阳县1017032885961122302614118.4026028.434.71奉节县903902762751589893854413.2215828.1628.38巫山县773541507161031752403810.2937025.5229.90巫溪县5826311796630406137856.2919

12、220.135.72黔江区4385201399431183716833710.3621432.5534.33武隆县15981914247055382373955.9220229.9436.19石柱县19847716718863355282758.8341923.0343.45秀山县43885514523952199400928.6214523.4438.28酉阳县11063918337995461254198.5626020.0335.57彭水县203829179654209276351506.6711521.3233.05实验七 SPSS主成份分析一、实验目的学习利用SPSS进行主成份分析二

13、、实验内容和步骤1、选 AnalyzeData ReductionFactor 进入主对话框；2、把变量选入Variables，然后点击Extraction,3、在Method选择一个方法（如果是主成分分析，则选Principal Components）,4、下面的选项可以随意，比如要画碎石图就选Scree plot，另外在Extract选项可以按 照特征值的大小选主成分（或因子），也可以选定因子的数目；之后回到主对话框（用Continue）。然后点击Rotation，再在该对话框中的Method选择 一个旋转方法（如果是主成分分析就选None），三、实验习题（二选一）1.下表为山东省2006

14、年统计数据，对此做主成分分析，找出主成分，并按 第一、第二主成分对山东省各城市进行综合排名，说明排名结果。表1山东省2006年统计数据单位：5元地 区:地区生产总值 第一产业增加值 第二产业增加值#工业增加值第三产业增加值济南市 青岛市 淄博市 枣庄市 东营市 烟台市 潍坊市 济宁市 泰安市 威海市 日照市 来无市 临沂市 德州市 聊城市 滨州市 荷泽市单位： 地区2185.09145.121001.783206.58183.951677.171645.1662.721079.06759.9568.48482.821450.3153.271170.132405.75216.011462.241

15、720.88211.811000.631456.09187.06803.441018.18116.28572.221368.53116.58849.59505.8773.89251.56291.9819.55192.401404.86178.65730.831003.38140.73559.51841.33138.84491.96833.6797.21514.82539.60166.44247.72各方面的支出（万元）流通部门 文体广播教育支出 科学支出861.511527.491003.00445.721115.031336.26916.51740.97503.54793.12220.071

16、80.59633.20504.00453.46471.75209.63医疗卫生：1038.191345.46503.38208.65226.91727.49508.44465.59329.68402.36180.4280.03495.38303.14210.54221.63125.44其他部门的事业费济南市11293124017593537377057235800青岛市351163853401744392568999134510淄博市18612743619013067014372331362枣庄市2711208568335315442476825433东营市112716566114045201

17、62390727969烟台市2163078822059936344937960217潍坊市9773648425229829743721143285济宁市21744633820446428584315946694泰安市13821967210346623583698024055威海市7171846812000412662956237796日照市70108145802410981657115238莱芜市3887588499806761301010942临沂市44753994619438027775172334332德州市14152008010043227773144216555聊城市36772623

18、410339923522763613616滨州市7591709610028410622493019961荷泽市41331410125664115233193161702.调查美国50个州7种犯罪率，得结果列于表35.2，其中给出的是美国50个州每100 000 个人中七种犯罪的比率数据.这七种犯罪是：murder （杀人罪），rape（强奸罪），robbery （抢 劫罪），assault （斗殴罪），burglary （夜盗罪），larceny （偷盗罪），auto （汽车犯罪），很 难直接从这七个变量出发来评价各州的治安和犯罪情况，试作主成份分析.说明选几个主成 分合适，找出几个主成分，并

19、按照第一、第二主成分分别对50个周进行排名，并解释之。表1美国50个州七种犯罪的比率数据state 州Murder杀人罪rape强奸罪robbery抢劫罪assault斗殴罪burglary夜盗罪larceny偷盗罪auto汽车犯罪ALABAMA14.225.296.8278.31135.51881.9280.7ALASKA10.851.696.8284.01331.73369.8753.3ARIZONA9.534.2138.2312.32346.14467.4439.5ARKANSAS8.827.683.2203.4972.61862.1183.4CALIFORNIA11.549.4287.

20、0358.02139.43499.8663.5COLORADO6.342.0170.7292.91935.23903.2477.1CONNECTICUT4.216.8129.5131.81346.02620.7593.2DELAWARE6.024.9157.0194.21682.63678.4467.0FLORIDA10.239.6187.9449.11859.93840.5351.4GEORGIA11.731.1140.5256.51351.12170.2297.9HAWAII7.225.5128.064.11911.53920.4489.4IDAHO5.519.439.6172.51050

21、.82599.6237.6ILLINOIS9.921.8211.3209.01085.02828.5528.6INDIANA7.426.5123.2153.51086.22498.7377.4IOWA2.310.641.289.8812.52685.1219.9KANSAS6.622.0100.7180.51270.42739.3244.3KENTUCKY10.119.181.1123.3872.21662.1245.4LOUISIANA15.530.9142.9335.51165.52469.9337.7MAINE2.413.538.7170.01253.12350.7246.9MARYLA

22、ND8.034.8292.1358.91400.03177.7428.5MASSACHUSETTS3.120.8169.1231.61532.22311.31140.1MICHIGAN9.338.9261.9274.61522.73159.0545.5MINNESOTA2.719.585.985.81134.72559.3343.1MISSISSIPPI14.319.665.7189.1915.61239.9144.4MISSOURI9.628.3189.0233.51318.32424.2378.4MONTANA5.416.739.2156.8804.92773.2309.2NEBRASKA3.918.164.7112.7760.02316.1249.1NEVADA15.849.1323.1355.02453.14212.6559.2NEW HAMPSHIRE3.210.723.276.01041.72343.9293.4NEW JERSEY5.621.0180.4185.11435.82774.5511.5NEW MEXICO8.839.1109.6343.41418.73008.6259.5NEW YORK10.729.4472.6319.11728.02782.0745.8