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(一)院系数学与统计学学院专业统计学年级2009级课程名称统计分析学号姓名__________________指导教师_____________2012年4月28日
(一)实验名称
1.编程计算样本协方差矩阵和相关系数矩阵;根据多元分析结果,P指小于,表明在的显着水平下,四个变量有显着差异
2.多元方差分析MANOVA
(二)实验目的
1.学习编制sas程序计算样本协方差矩阵和相关系数矩阵;
2.对数据进行多元方差分析
(三)实验数据第一题xl x2x3x4x5x6x7446217818240621851854445156168424016617238551781804758176176407017618043641621704463174176384817018644451681684556186192455117617647471621645450166170494418018551571681725110481621684848162164497616816857581741765462156165524816416650481461555148172172541681724451591861885749148155495618618848521701765253170172第二题:kind xl x2x3x41125603382101119802333301635126020316551429150113065403205169453501901466058520011466627325018754585240111077507270110760364200113061391200180454292701605044219018154260280113587507260157484002851755252026017665403250155411170422665445531028245403210265653122802405147728026754481293238504682102424535119021134039031028055520200276605071892943326028026051429190255403902952654848117726948442225212563312270212056416280270454683702626641622426960377280365334802603100344682953656341626531174846825031146339538035530546235364515073203110904422253606244024831106937726038878299360373633903203114554942403103544163103100332733123140613123453803628625031355446834531306932536036057273260
(四)实验内容
1.打开SAS软件并导入数据;
2.编制程序计算样本协方差矩阵和相关系数矩阵;
3.编制sas程序对数据进行多元方差分析;
4.根据实验结果解决问题,并撰写实验报告;
(五)实验体会(结论、评价与建议等)第一题程序如下proc corrdata=cov;proc corrdata=nosimple cov;with x3x4;partial xl x2;run;结果如下:7变量xl x2x3x4x5x6x7协方差矩阵,自由度=30xl x2x3x4x5xG x7xl xl
27.1591398-
10.1364946-
8.
45626451.364709-
6.1193548-
18.0516129-
20.6752688x2x2-
10.
136494669.3650389-
7.
22105081.
65825471.
568204315.
498655919.0337204x3x3・
8.4562645-
7.
221050828.3793848-
6.3725471-
15.3064183-
21.7352376-
11.5574785x4x
41.
36470971.6582547-
6.
37254711.
92491784.
60930114.
46124732.8747634x5x5-
6.
11935481.5682043-
15.
30641834.
609301168.
797849527.
038709719.5731183x6x6-
18.
051612915.4986559-
21.
73523764.
461247327.
0387097105.
103225887.3505376x7x7-
20.
675268819.0337204-
11.
55747852.
874763419.
573118387.
350537683.9806452SAS系统CORR过程08:15Friday,April28,200011协方差矩阵2相关系数矩阵Pearson相关系数,N=31当HORho=0时,Prob|r|xlx2x3x4x5x6x7xl
1.00000-
0.23354-
0.
304590.18875-
0.14157-
0.33787-
0.43292xl
0.
20610.
09570.
30920.
44750.
06300.0150x2-
0.
233541.00000-
0.
162750.
143510.
022700.
181520.24938x
20.
20610.
38170.
44120.
90350.
32840.1781x3-
0.30459-
0.
162751.00000-
0.86219-
0.34641-
0.31797-
0.23874x
30.
09570.
3817.
00010.
05630.
02660.1997x
40.
188750.14351-
0.
862191.
000000.
400540.
313650.22610x
40.
30920.
4412.
00010.
02560.
08580.2213x5-
0.
141570.02270-
0.
346410.
400541.
000000.
317970.25750x
50.
44750.
90350.
05630.
02560.
08130.1620xG-
0.
337870.18152-
0.
397970.
313650.
317971.
000000.92975x
60.
06300.
32840.
02660.
08580.
0813.0001x7-
0.
432920.24938-
0.
236740.
226100.
257500.
929751.00000x
70.
01500.
17610.
19970.
22130.
1620.0001第二题:程序如下:proc anovadata=;class kind;model xl-x4=kind;manova h=kind;run;结果如下1分组水平信息The ANOVAProcedureClass LeveIInformat ionCIass LeveIsVaiueskind3123Number ofobservat ions602xlx
2、x
3、x4的方差分析Dependent Variablexl xlSum ofMean SquareF ValuePrFSource DF Squares
2610.
650003.
380.0411Model
25221.
30000773.15000Error
5744069.55000The ANOVAProcedureR-Square CoeffVar RootMSE xlMean
85.95000R-Square CoeffVar RootMSE x2Mean
0.
05364222.
9988812.
6685555.
083330.
10592832.
3508727.80557Source DFAnova SSMean SquareF Valuekind
25221.
3000002610.
6500003.38The ANOVAProcedureDependent Variablex2x2Sum ofSource DF SquaresMean SquareF ValueModel
2518.
533333259.
2666671.62Error
579148.
050000160.492105Corrected Total
599666.583333PrF
0.0411Source DFAnova SSMean SquareF ValuePrFkind
2518.
5333333259.
26666671.
620.2078PrF
0.2078dependent Variablex3x3The ANOVAProcedureSource DFSumofSquaresMean SquareF ValuePrF
2480.8333Model
21240.
41670.
170.
8478427028.5000Error
577491.
7281429509.3333Corrected Total59R-Square CoeffVar RootMSE x3Mean
0.
00577621.
1798086.
55477408.6667Source DFAnova SSMean SquareF ValuePrFkind
22480.
8333331240.
4166670.
170.8478The ANOVAProcedureDependent Variablex4x4Sum ofSourceDFSquaresMean SquareF ValuePrFModel
238529.
300019264.
65008.
010.0009Error
57137115.
10002405.5281Corrected Total
59175644.4000R-Square CoeffVar RootMSEx4Mean
0.219360SourceDFAnova SSMean SquareF ValuePrF
19264.
650008.
010.0009kind
238529.
3000018.
9660449.
04618258.6000
(3)多元方差分析The ANOVAProcedureMultivariate Analysisof VarianceCharacteristicRoots andVectors ofE InverseH,where米H=Anova SSCPMatrix forkindE=Error SSCPMatrixCharacterist icCharacteristic VectorV,EV=1Percent x3x4Root xlx
20.
3360453873.17-
0.00045795-
0.
003790960.
000303660.
002793390.
1232338326.
830.
004241110.
002368780.
000018420.
000028320.
000000000.
000.00121062-
0.
000324010.00157046-
0.
000065390.
000000000.00-
0.
003177980.
010435260.
000070140.00076972MANOVA TestCriteria andF Approximationsfor theHypothesis ofNo OveralIkind EffectH=Anova SSCPMatrix forkindE=Error SSCPMatrixS=2M=
0.5N=26Stat istic ValueF ValueNum DFDen DFPrFWilks Lambda
0.
666359531080.0040Pillais Trace
0.
361235851100.0041Hotel Iing-Law leyTrace
0.
4592792174.
8560.0048Roys GreatestRoot
0.
33604538550.0027NOTEF Statisticfor Roys GreatestRoot isan upperbound.NOTEF Statisticfor WilksLambda isexact.4333•■■■60002734。