sas數(shù)據(jù)分析結(jié)果

1、SAS 結(jié)課論文SAS是在1960年代末期由兩位北卡州立大學(xué)(NorthCarolinaStateUniversity)統(tǒng)計(jì)系的教授開發(fā).第一版的SAS只含一般線性模型的分析法，而且只適用于舊M的主機(jī)；1976年成立SAS公司負(fù)責(zé)軟件的發(fā)展、維護(hù)并提供相關(guān)服務(wù).PC版本的SAS于1987年推出(V6.02),1989年推出SAS/PC(V6.04)版本；1997年下半年推出適用于多種操作系統(tǒng)的V6.12版本（Windows版）；2000年2月又推出SAS系統(tǒng)V8版本，2001年推出SAS系統(tǒng)V8.2版本；目前SAS最新版本為V9.01.在眾多的統(tǒng)計(jì)軟件中，SAS以運(yùn)行穩(wěn)定、 功能強(qiáng)大而著稱。

2、近20年來(lái)，SAS一直占據(jù)著統(tǒng)計(jì)軟件的高端市場(chǎng)，用戶遍及金融、醫(yī)藥衛(wèi)生、生產(chǎn)、運(yùn)輸、通訊、政府和教育科研等領(lǐng)域。在數(shù)據(jù)處理和統(tǒng)計(jì)分析領(lǐng)域，SAS系統(tǒng)被譽(yù)為國(guó)際上的標(biāo)準(zhǔn)軟件，堪稱統(tǒng)計(jì)軟件界的巨無(wú)霸。在國(guó)際學(xué)術(shù)界有條不成文的規(guī)定，凡是用SAS計(jì)分析的結(jié)果，在國(guó)際學(xué)術(shù)交流中可以不必說(shuō)明算法，由此可見其權(quán)威性和信譽(yù)度。SAS的功能模塊：SAS系統(tǒng)由三十幾個(gè)模塊組成，其分析功能散布在幾乎 所 有 的 模 塊 之 中 ， 較 為 集 中 的 具 有 統(tǒng) 計(jì) 分 析 功 能 的 是SAS/BASESAS/STATSAS/QCSAS/INSIGHTSAS/ET濤一些模塊， 通過(guò)編程可以調(diào)用各種分析功能。對(duì)于常

3、用的一些統(tǒng)計(jì)分析方法，SAS系統(tǒng)中的如下三種方法可以達(dá)到同樣的目的：INSIGHT（交互式數(shù)據(jù)分析”）Analyst（“分析家”）直接編程方法一：區(qū)間分析1.點(diǎn)估計(jì)和區(qū)間估計(jì)參數(shù)的估計(jì)方法主要有兩種：點(diǎn)估計(jì)和區(qū)間估計(jì)。點(diǎn)估計(jì)是用樣本的觀測(cè)值估計(jì)總體未知參數(shù)的值。由于樣本的隨機(jī)性，不同樣本觀測(cè)值計(jì)算得出的參數(shù)的估計(jì)值間存在著差異，因此常用一個(gè)區(qū)間估計(jì)總體的參數(shù)， 并把具有一定可靠性和精度的估計(jì)區(qū)間稱為置信區(qū)間。利用構(gòu)造的統(tǒng)計(jì)量及樣本觀測(cè)值，計(jì)算得出參數(shù)的置信區(qū)間的方法稱為參數(shù)的區(qū)間估計(jì)。2,參數(shù)的置信區(qū)間在區(qū)間估計(jì)中，對(duì)于總體的未知參數(shù)0,需要求出兩個(gè)統(tǒng)計(jì)量01（X1,X2,.,Xn）和02（X

4、1,X2,.,Xn）來(lái)分別估計(jì)總體參數(shù)0的上限和下限，使得總體參數(shù)在區(qū)間（01,02）內(nèi)的概率為P010t-17.93d198.0001結(jié)果顯示，無(wú)論兩總體的方差是否相等，t統(tǒng)計(jì)量的p值=0.00050.05,所以在95%勺置信水平下，拒絕原假設(shè)，兩總體的均值有顯著差異。結(jié)果表明可以95%勺把握認(rèn)為股票中最新和昨收有顯著差異。方法二：回歸分析1.回歸模型變量Y與其他有關(guān)變量X1,X2,Xk的關(guān)系Y=f(X1,X2,Xk)+稱為“回歸模型”，其中為均值為0的隨機(jī)變量。當(dāng)f為meiiyijlaiMlyljIa2線性函數(shù)時(shí)，回歸模型：Y=0+1X1+2X2+,+kXk+稱為線性回歸模型，本章主要討論

5、線性回歸模型。特別地，當(dāng)k=1時(shí)稱為一元線性回歸模型。2 .回歸分析的內(nèi)容與目的建立變量Y與X1,X2,Xk的經(jīng)驗(yàn)公式(回歸方程，預(yù)測(cè)公式)，即從一組樣本數(shù)據(jù)出發(fā)，確定出變量之間近似的數(shù)學(xué)關(guān)系式；對(duì)經(jīng)驗(yàn)公式的可信度進(jìn)行檢驗(yàn)；判斷每個(gè)自變量Xi(i=1,2,k)對(duì)Y的影響是否顯著；對(duì)經(jīng)驗(yàn)公式進(jìn)行回歸診斷(診斷經(jīng)驗(yàn)公式是否適合這組數(shù)據(jù))；利用合適的經(jīng)驗(yàn)公式，根據(jù)自變量的取值對(duì)因變量的取值進(jìn)行預(yù)測(cè)。3 .線性回歸模型(LineRegressionmodel)線性回歸模型的一般形式為：Y=0+1X1+,+kXk+其中0,1,k,是未知的參數(shù)，是不可觀測(cè)的隨機(jī)變量，稱為誤差項(xiàng)，假定N(0,2)。如果有n

6、次獨(dú)立的觀測(cè)數(shù)據(jù)(xi1,xi2,xik;yi)i=1,2,n,則線性回歸模型可以表示成如下形式：1=p0+P1X11+P2X12+.+PkX1k+SIy2=鳧+P1X21+P2X22+十0kX2k+%I.yn=B,-1Xn1=Xn2 其中1,2,n相互獨(dú)立且服從N(0,2)分布上式可以簡(jiǎn)寫成如下矩陣形式：Y=X(3+其中(1)分析步驟選擇主菜單“StatisticsRegression”“Linear”打開“LinearRegression(線性回歸)”對(duì)話框，按順序進(jìn)行多元線性回歸分析；此時(shí)顯示的分析結(jié)果表明模型的作用是顯著的(F統(tǒng)計(jì)量的值為1.072E7,p值0.0001FModelEr

7、rorCorrectedIdial5193 儂2.078762El111J6S997E131J8I7S4E1341575236952S031070S3990.690.6321RootMSEDependentCoeffV&rMMFI246582208782117.82650R-SquareAdjR-Sq0.0176-O.OD79ParfirweterEslimatesVariableLtibellParameter*EstfiwateStandardError(V&luePrlt|InterceptIntarcapl1-537E22416211462-B.33CHBREJii&a

8、mp;a1iBHEctienEjiftc1i&jn&1-0.088960J2957-0.B90.4184ma.iyijialmaayiJial113490132157931D.630.6328Miyi屈it&iyiji 般1-7000562264336-D.310.7585naiyi1tanglmalyi1langl1-M.3529032.73272M.440.6615被 tiyi1Ian 算Italy)1Iani2130 邢 5 詞24.223481.270,2066(2)逐步回歸“分析家”中選擇變量的方法很多，在上述步驟的“LinearRegression”對(duì)話框中

9、，單擊Model按鈕,打開“LinearRegression:Model”對(duì)話框。在“Method”選 項(xiàng) 卡 中 包 含 多 種 變 量 的 選 擇 方 法 ， 選 擇 其 中 一 種 ， 例 如 選 擇“Backwardelimination.此時(shí)顯示的分析結(jié)果為：TheREGPnocedureModal:MD0EL1DependentVeiri&ble：cbengjiaaechtnejieioeBackwardElimination：&UP0AlIVariablesEntered：R-Square=D.0175andC(p)=6.0000-ialvsisofVarianc

10、eSourceDFSumofSquaresMeanSquareFValuePrFModel52.0787C2E11415752368520.690.6321Error1931.163397E1880810706389CorrectedTotti1981.184784E13BackwardElimination：Step1參數(shù)估計(jì)部分表明擬合的回歸方程為：Chengjiaoe=-216182+86064194chengjiaoliang+28998maiyijia1-3865.91895maiyijia2+0.14257maiyiliang1-0.09443maiyiliang2模型的R2為1.

11、0000,C(p)值較小(僅為6.0000);方差分析中模型的作用也是顯著的(F統(tǒng)計(jì)量的值為1.072E7,p值0.0001FIntercept-53762416211楣26304626660.110.7406chencJ1ao1iang-0.0899512857290621700720.450.43S4值*iyijEl13490132157331F35695第3310.390.5326ilyljI&2-700066225433658169836180.100.7565ikai/i1iangl-14.3529032,78272115860351710.190.6B15nai/i1i電n

12、g?30,6855924.22348968441411031.610.20GGBoundsoncoriditionlumber：1.7523,83.086chengjiaoechengjiaoliangmaiyijia1maiyijia2maiyiliang1maiyiliang210272801019168.618.6211075618080630388.618.62241756234240942038.618.62268707482161265698.618.622387071498561359378.618.62163695465256124578.618.621737521101651

13、1178.618.62228290117104442438.618.621422892947841899998.628.637141388655201252908.628.636431383112920871578.628.6353313828624582108.628.63595138453448526678.628.6378113903339841699738.628.6378110036500481169848.628.632089191366336284948.618.6217082670704471638.618.621610131095841086848.618.621610163

14、620321509948.618.6215691222156241290958.618.621594116637446471678.618.62157693585842493628.618.621545356473272629358.628.6325110123288820038.628.63251124148320792948.618.621531177601269678.628.63961221137096814378.628.631061182306640127278.618.6314091226206752968328.628.63331457451288584628.628.6320

15、1053138000701708.618.6215703699208287628.628.638100719989612649778.618.6214902460336907168.618.621480114112936488078.618.63149099284480392778.628.631019921327681445118.628.63899434480479518.618.62150049259456291218.618.621497100888776216448.618.6215259491939522118778.618.621505892353442984218.618.62

16、15051000320536368488.618.62138810348182472168.618.621327127548216646178.618.62127212869475257038.618.621207163443104261638.618.6212101611234408194058.618.6211521441105112233848.618.6211041528105056282798.618.6211121541439442345738.618.621091151794736216728.618.621024157155968338528.618.6210191568112

17、000289688.618.62104115718531281068.618.6210121519734968427478.618.6279198727552166538.618.627591006235096464148.618.621145984282664809548.618.6211346561455523362418.618.621036631228376120608.618.6297942663720547648.618.62951460120616121898.618.628923615106801914088.618.62532315181792238408.618.62502

18、218126576100608.618.62405377125824296258.618.62382262150728496438.618.6229828556626461828.68.62152227372344222388.68.61152235172093508.68.611520105171320876568.68.61150515445632733958.68.61150513455944659238.68.6114592084904076238.68.611435224281536621398.68.61143424106720102628.618.6217100588744203

19、458.618.62619521015922003648.68.61140657188376233408.68.611332115189208202018.68.61112811817735284638.68.6211129822291841588168.618.621778912520183618.68.612698617200105628.68.61252202487144127878.68.61951182228481364658.598.6137635346112496088.68.6123109723281418.68.611412071424102128.68.6132417837

20、024128698.68.61463350178920671648.68.6144631259352282328.68.61487302383056672498.618.62217167286160228938.618.6225616102152881129448.618.62159157217481622838.618.6261536227968694958.68.61631139209888867928.68.61481159811184104178.68.6147826231231122206608.68.614442857513432110888.598.612126741668401

21、066788.598.612221070146200131898.598.612221036125560133968.598.6124413465332059818.598.61259130155904869558.598.614761250176296102618.598.6147610591266744216188.68.611074379620640222168.68.6113063796584961149928.68.61138338021209160256438.68.6128379791200102388.598.6145241451088658698.68.61104355432

22、06082075178.598.68793958600385208.598.687939711264070308.598.686370318920137458.598.6863742109224470158.598.686567543000175028.598.6865107110485690428.598.6920107510320279488.598.6934137250736236918.598.6147014044124893108.598.616521435179280271558.598.61741129241837693398.598.6132114703206402444658

23、.598.611891478180416498108.598.610941522119424129818.598.6995187951287263958.598.64491842207168638298.598.63701739181336105108.598.62471658112883228258.588.59106818554120530568.588.591105194210032156658.598.654613308592208948.598.656611501444001771438.598.66221071187456274088.598.6116287461072121898

24、.598.61390868180472425068.598.61575782487144751908.618.61228756222848230378.618.61142707346112192988.618.62714707972321188698.618.62643695714242144928.618.6153337537024473658.618.61595290178920116558.628.6178113845935280838.628.6216101390383056366148.628.621610100386160151768.628.6115699192152881870

25、28.628.61159426174816319008.628.6115761322796898238.628.6154516320716828368.618.612593181336264408.618.61253561128832188058.618.611531110154120622208.618.62961124210032151518.618.6210618592827908.618.6281221144400303648.618.6214901182187456459278.628.62148012266107229788.628.6214901457180472769688.618.621011053487144122758.628.638100822284841198.628.631500949346112218608.618.631497892