典型相关分析报告SPSS例析Word文件下载.docx

1、2S1S50003貂3G01.2S3.002.3315904G0Q3 172401 752 ?12 509D019352.50460760020001 OO1 0Q2 712 OQ数据的格式如上所示，以下对三组变量两两做典型相关分析。首先对公司规模和 CRM实施程度做典型相关分析SPSS并未提供典型相关分析的交互窗口，只能直接在 synatx editor窗口中呼叫SPSS的CANCORR程序来执行分析。并且 cancorr不能读取中文名称，需将变量改为英文名称。打开文件后File- newsynatx editor 打开语法窗口输入语句INCLUDE D:spss19SamplesE ngl

2、ishCa nonical correlatio n.sps.CANCORR Set仁Cap ital Sales/Set2=Web Mail Call DM Mobile ShortM.小写字母也行，但是变量名字必须严格一致in clude spss19SamplesE nglishCa non ical correlati on. sps. can corr set仁Capital Sales/set2=Web Mail Call DM Mobile ShortM.注意第三行的“ / ”不能为“ ”鳩D：转换T 分析X 直騎I：圈形:C；实用程序2 逶召貳、工具 窮讥：帮助3 canoni

3、cal correlation aciivfe daia *include D.3p33l9.Saniple3 EnglishCanonical correlatino.sps cancorr setlCaprtal SEes VS5t=Wsb Ma Ca DM Mobile ShortMrun all得到典型相关分析结果CcrrelaTic ris for CapitalCapital 1.0000 -7143Sales .7143 1.0000第一组变量间的简单相关系数Correlations forWb Mail Call DM Mobile ShcrtMWt 1.0000 .3991

4、.493S .禿 42 ,115 月5 汚Mail .3991 l.OOCO 3776 .3176 .3374 .3538Call .43*38 .3776 1.0000 .6463 .5342 .6278DM .3842 .3176 .6463 1.0000 .3578 .4961Mobile ,1815 ,3374 ,5342 35疋 1.0000 应出ShortM .3535 .3338 ,&278 -49frl .6250 1.0000Correlations Betee口 St-1 and Set-2Wt Maiil 匚訓 DM Mobile ShortMCapital .273S

5、.1733 ,3189 .1873 ,31t0 .2374Sals .1876 .L343 ,2597 .2260 .3969 .3409Canonical Correlations1.434.298CR2=0.298.Test that remaining correlations are zero: Wilks Chi-SQ OF Sig.7弱 20.33 12.000 .0S0此为检验相关系数是否显著的检验，原假设：相关系数为 0.每行的检验都是对此行及以后各行所对应的典型相关系数的多元检验。0的，相关性显著。第二行 sig值第一行看出，第一对典型变量的典型相关系数是不为P=0.2630

6、.05 ，在5%显著性水平下不显著。Standardized Canonical Coefficients for Set-11 2Capital -,287 -1,400Saks -.774 1.201 feA Canonical Coefficients foSr-LCapital .000 .0005al-fi5 .000 .000第一个典型变量的标准化典型系数为 -0.287和-0.774.CV1-2=-1.4capital+1.2salesCV1-1=-0.287capital-0.774sales,Staindardifd Cari?nial foSet-2We b-341,43：

7、.117-.168Call.027-1.075-.091.490Mobile -.767 .1390.091DM 0.767mobile 0.174shortmShortM L74 .812Raw Canonical Coefficients for Sec-2険t.-.330-.419,101 -斗5.019 -.762-074.398-37.152-.154.763CV2-1=-0.341web+0.117mail+0.027callCV2-2=-0.433web 0.168mail 1.075call+0.490DM+0.139mobile+0.812shortmCanonksl Loa

8、dirig for Set-2他b-516-S30Miil-.354-.273-.674-.451-527.028F-lobile-917115Short M-飞5Canonical Loadings For ST-1-.841-.542Cross Loa-dina j7for Set-2Sak5-.980,201W-eb-224-丄58-,081Cross Loadings for Sec-1-.293.134-.229.008-.365-.152-398.034-425.060-332.077典型负荷系数和交叉负荷系数表Redundancy Analis:Proportion of Var

9、ianc电 of SeT-1 Exp:daind by Its Own Can. Var.Prop VarCV1-1 .833GV1-2 ,1S7Proportion of Vari a rice of ST-1 Ex 匚 Jained by Opposite Can .VanPirop VarCV2-1 .157CV2-2 .015Proporrion of -Arianes 凸f 5飢一2 Eyplaind by Ir; O训r Can. Var.CV2-1 .425CV2-2 .107PrQpQrtiQn qF Vrinc f Stt一2 Explained by OppQsit Can

10、、耳小CVll ,080CV1-2 .003重叠系数分析Redu nda ncy in dex0.157= CR1 *0.833=0.434人2*0.8330.08= CR12 *0.425 =0.434A2*0.425| 81_CV001S2_CV001S1_CV002S2_CV002-06-98.02-56-23-1 33*.10-J81 95-.03-1 SO-13-1 9900”1 69-05-1 41-01-1 16r20-1 23rs a电己电o;AliksChi-SQOF 5?ig.744.36869.03318.000.000.339n,82313.4S110,000.1993

11、.265.9305.0114.000.286CRM绩效与CRM实施程度典型相关分析自变量因变量规则相关系数 检验的P值公司规模CRM实施程度0.4340.05CRM绩效0.3680.000.3580.112由上表知，公司规模与CRM实施程度显著相关，且公司规模越大实施程度越高； 此外CRM 实施程度越高越能实现 CRM绩效，但公司规模与 CRM绩效并不显著相关；就整体而言， 公司规模不直接影响 CRM绩效，而是通过CRM实施程度间接影响 CRM绩效。影响CRM 绩因素很多，光靠较大公司规模还不是 CRM绩效的保证，还有其他因素影响 CRM绩效。例2 :全国30省市自治区农村收入与支出的指标，

12、x1 x4反映农村收入，y1-y8反映农村生活费支出，对收入与支出进行典型相关分析。- 垃乂4 J1 Y1 IyJ234.210.7452.49353S625427Q.6G惟福建520.641295.96113.16113 931093.4599.1?215江西319 691161.47J1 6914 &774 61TO 271&山东408 981230 5646 7728 78748 68102 032oe163.611004 1935 8223.45544.2677.07131湖北192 36123 8747 5133 48753 9181 11湖南263 001095 6946 1615

13、 11823 9173 61192广东712 241756.74180.3050 061220.0091.3134FJ B202 W1158 0674 541144760 2649 1713S海南53 571307 8633 9774,31737 2143 OS32E III的A胎RM xdA7仍詰71R 111刃 名称匚婪型宽度匚小数| 标签 |area字符弗地区xl数值6茅动者很酬（元：x2数值（N）S家庭经营腋入（.:数直啊）轉移性收入（ffi.：x4Kfi（N）财产性收入（无:yiMIN）食品盍出元）：衣看支出畀）：y3数值1）呂居住支出元）:y4塞庭锻备及服务:y5医疗保健支岀:ye

14、S?H（N）8交通和通讯支出：車Ktt（N）Z文教f娱乐用品一:其他商品及服务语法输入/spss19/Samples/E nglish/Ca nonical correlatio n.spscan corr set1=x1 x2 x3 x4/set2=y1 y2 y3 y4 y5 y6 y7 y8.Corrlati*ns for St-1X1 2煜 x =i x4乂 11.0000逸6,73S1701.3586.4369,3673x3.73814391,0000,4867.5701.3673.4857Co rrelati : n s fc r SetrZy2 y3*X V7viL0000.71

15、93.8492.8837.6331.896?.8980.3772y2hOOOOS273.8328.7500.8144,6825.7846V3.84 92.72731.00G0.6061.9150. i 55.3073 883_,832844E.SO.5061.63621.000Q.6615.6381.6869y6 89S5,8144,91508739,9307V7.6825产 c.J / DD,8446.6981.3739l.OOOG.7921V8.8772,7846,3073.9080KB69.3307J981l.OOCO1.3822,9ia35964Tst That remaining c

16、o rr I at io ns are zero:WilkDF Sic.,003132.9S132.000,000.07658.10521.000,44218.38112-000.6858.5015.000.131只有前两对典型相关系数是显著的；分别为 CR1=0.982和CR2=0.910.Standardized Canonical Coeffitierrts fr Set-12 3,511-1,046-L.G34,933-.4481.459-.150,179-.142-315-.887.806CV1-1=-0.511x1-0.039x2-0.448x3-0.142x4CV1-2=-1.0

17、46x1-0.293x2+1.459x3-0.319x4Standardized 匚anonical 匚o-sffiients for Set-2-.199-.1171.553V2.017-1.512-1.240.614泊.斗42-L.51H1-002-总5V4-.615L32O1 011-2.446.096-.0311.063-137西-.415.70S-L.43-.326y7-.070.453-1.054,943-.220.274541364CV2-1=-0.199y1+0.017y2+0.442y3-0.615y4+0.096y5-0.415y6-0.07y7-0.22y8CV2-2=-

18、0.117y1-1.512y2-1.515y3+1.320y4-0.03y5+0.705y6+0.453y7+0.274y8第一对典型变量说明靠劳动报酬和转移收入为主的家庭其对应的消费主要在家庭设备和服务，交通和通讯支出上，在居住支出上比较少。例三：已知294个被调查者的 cesd （抑郁症）health 与sex , age ,education,income 组指标建立数据文件。对两组进行典型相关分析。/spss19/Samples/E nglish/Ca non ical correlatio n.spsCANCORR Set 仁 cesd health/Set2=sex age edu

19、c in come.结果选录Canonkal Correlations1 .4052 .266Test that remaining correlations zero: Wilks Chi-SQ DF 百ig.1 .777 73,037 8.000 .000.929 21,165 3.000Standardized Canonical Coefficients fc-r Set-Lcesd -.490health ,382 -288Siandardized Canonical 匸nts for Sec-2S4X ,025 -.396age .871 ,443educ -.383 .448income .082 .555从第一对典型变量的表达式看出，年龄较大， 教育程度较低，相对的无抑郁症趋势；显然健康比较差。第二对典型变量表明，年龄小，教育度低，收入低的女性相对的有抑郁症。