數(shù)據(jù)分析實驗報告分析解析

試驗課程： 數(shù)據(jù)分析專 業(yè)：信息與計算科學(xué)班 級：學(xué) 號：姓 名：中北大學(xué)理學(xué)院試驗一SAS【試驗?zāi)康摹苛私釹AS系統(tǒng)，嫻熟把握SAS數(shù)據(jù)集的建立及一些必要的SAS語句?！驹囼瀮?nèi)容】SCOREtest。SCORENameSexMathChineseEnglishAlicef908591Tomm958784Jennyf939083Mikem808580Fredm848589Katef978382Alexm929091Cookm757876Bennief827984Hellenf857484Winceletf908287Buttm778179Geogem868582Todm898484Chrisf898487Janetf866587將SCORE數(shù)據(jù)集中的記錄依據(jù)math的凹凸拆分到3個不同的數(shù)據(jù)集：math80bad3good，normal，bad【試驗所使用的儀器設(shè)備與軟件平臺】SAS【試驗方法與步驟】1：DATASCORE;INPUTNAME$Sex$MathChineseEnglish;CARDS;2Alicef908591Tomm958784Jennyf939083Mikem808580Fredm848589Katef978382Alexm929091Cookm757876Bennief827984Hellenf857484Winceletf908287Butt m778179Geoge m868582Tod m898484Chris f898487Janet f866587;Run;PROCPRINTDATA=SCORE;DATAtest;SETSCORE;2：DATADATAgoodnormalbad;SETSETSCORE;SELECTSELECT;whenwhen(math>=90)outputgood;whenwhen(math>=80&math<90)outputnormal;whenwhen(math<80)outputbad;endend;RunRun;PROCPRINTDATA=good;PROCPRINTDATA=normal;PROCPRINTDATA=bad;3：DATAAll;SETSETgoodnormalbad;PROCPROCPRINTDATA=All;RunRun;3【試驗結(jié)果】結(jié)果一：結(jié)果二：4結(jié)果三：5試驗二 上市公司的數(shù)據(jù)分析【試驗?zāi)康摹縎AS軟件對試驗數(shù)據(jù)進展描述性分析和回歸分析，生疏數(shù)據(jù)分析方法，培育學(xué)生分析處理實際數(shù)據(jù)的綜合力量。22023年的每股收益ep2023年最終一個交易日的收盤價(price).代碼2流通盤某上市公司的數(shù)據(jù)表每股收益股票價格00009685000.05913.2700009960000.02814.200015012600-0.0037.12000151105000.02610.0800015325000.05622.7500015513000-0.0096.8500015636000.03314.95000157100000.0612.65000158100000.0188.3800015970000.00812.15000301153650.047.3100048877000.10113.2600072560000.04412.3300083513380.0722.5800086932000.19418.290008777800-0.08412.550008856000-0.07312.48000890169340.0319.12000892120230.0317.88000897141660.0026.91000900214230.0588.5900090148000.00527.950009026500-0.03110.9200090360000.10911.7900090595000.0469.2900090666500.00714.4700090889880.0068.2800090960000.0029.9900091080000.0368.900091172800.0679.01000912150000.1128.0600091384500.06211.8600091545990.00114.4000916340000.0385.15000917118000.08616.230009186000-0.04510.1261、對股票價格計算均值、方差、標(biāo)準(zhǔn)差、變異系數(shù)、偏度、峰度；計算中位數(shù)，上、下四分位數(shù)，四分位極差，三均值；作出直方圖；作出莖葉圖；進展正態(tài)性檢驗〔W；7〕計算Spearman相關(guān)矩陣；8〕分析各指標(biāo)間的相關(guān)性。值及殘差；給定顯著性水平α=0.05，檢驗回歸關(guān)系的顯著性，檢驗各自變量對因變量的影響的顯著性；擬合殘差關(guān)于擬合值YXX及XXQQ1 2 1 2這些殘差，并予以評述?！驹囼炈褂玫膬x器設(shè)備與軟件平臺】SAS【試驗方法與步驟】datadataprices;inputinputnumscaleepsprice;cardscards;00009685000.05913.2700009960000.02814.200015012600-0.0037.12000151105000.02610.0800015325000.05622.7500015513000-0.0096.8500015636000.03314.95000157100000.0612.65000158100000.0188.3800015970000.00812.15000301153650.047.3100048877000.10113.2600072560000.04412.3300083513380.0722.5800086932000.19418.2970008777800-0.08412.550008856000-0.07312.48000890169340.0319.12000892120230.0317.88000897141660.0026.91000900214230.0588.5900090148000.00527.950009026500-0.03110.9200090360000.10911.7900090595000.0469.2900090666500.00714.4700090889880.0068.2800090960000.0029.9900091080000.0368.900091172800.0679.01000912150000.1128.0600091384500.06211.8600091545990.00114.4000916340000.0385.15000917118000.08616.230009186000-0.04510.12run;PROCPROCPRINTDATA=prices;runrun;procprocmeansdata=pricesmeanvarstdskewnesskurtosiscv;varvarprice;outputoutputout=result;runrun;procprocunivariatedata=pricesplotfreqnormal;varvarprice;outputoutputout=result2;runrun;procproccapabilitydata=pricesgraphicsnoprint;histogramhistogramprice/normal;runrun;procproccorrdata=pricespearsonspearmancovnosimple;varvarprice;withwithprice;runrun;procprocregdata=prices;modelmodelprice=scaleeps/selection=backwardnointpr;outputoutputout=pricesp=pr=r;procprocprintdata=prices;8runrun【試驗結(jié)果】91011對于問題二結(jié)果：121314試驗三50軟件對試驗數(shù)據(jù)進展主成分分析和因子分析，生疏數(shù)據(jù)分析方法，培育學(xué)生分析處理實際數(shù)據(jù)的綜合力量?！驹囼瀮?nèi)容】350100000個人中七種犯罪的比率數(shù)Murder〔罪，Rape〔罪，Robbery〔罪，Assaul〔斗毆罪，Burglar〔夜盜罪，Larcen〔偷盜罪，Auto〔汽車犯罪表3 美國50個州七種犯罪的比率數(shù)據(jù)StateMurderRapeRobberyAssaultBurglaryLarcenyAutoAlabama14.225.296.8278.31135.51881.9280.7Alaska10.851.696.8284.01331.73369.8753.3Arizona9.534.2138.2312.32346.14467.4439.5Arkansas8.827.683.2203.4972.61862.1183.4California11.549.4287.0358.02139.43499.8663.5Colorado6.342.0170.7292.91935.23903.2477.1Connecticut4.216.8129.5131.81346.02620.7593.2Delaware6.024.9157.0194.21682.63678.4467.0Florida10.239.6187.9449.11859.93840.5351.4Georgia11.731.1140.5256.51351.12170.2297.9Hawaii7.225.5128.064.11911.53920.4489.4Idaho5.519.439.6172.51050.82599.6237.6Illinois9.921.8211.3209.01085.02828.5528.6Indiana7.426.5123.2153.51086.22498.7377.4Iowa2.310.641.289.8812.52685.1219.9Kansas6.622.0100.7180.51270.42739.3244.3Kentucky10.119.181.1123.3872.21662.1245.4Louisiana15.530.9142.9335.51165.52469.9337.7Maine2.413.538.7170.01253.12350.7246.9Maryland8.034.8292.1358.91400.03177.7428.5Massachusetts3.120.8169.1231.61532.22311.31140.1Michigan9.338.9261.9274.61522.73159.0545.5Minnesota2.719.585.985.81134.72559.3343.1Mississippi14.319.665.7189.1915.61239.9144.4Missouri9.628.3189.0233.51318.32424.2378.4Montana5.416.739.2156.8804.92773.2309.2Nebraska3.918.164.7112.7760.02316.1249.1Nevada15.849.1323.1355.02453.14212.6559.2NewHampshire3.210.723.276.01041.72343.9293.4NewJersey5.621.0180.4185.11435.82774.5511.5NewMexico8.839.1109.6343.41418.73008.6259.5NewYork10.729.4472.6319.11728.02782.0745.8NorthCarolina10.617.061.3318.31154.12037.8192.115Ohio7.827.3190.5181.11216.02696.8400.4NorthDakota0.99.013.343.8446.11843.0144.7Oklahoma8.629.273.8205.01288.22228.1326.8Oregon4.939.9124.1286.91636.435061388.9Pennsylvania5.619.0130.3128.0877.51624.1333.2RhodeIsland3.610.586.5201.01489.52844.1791.4SouthCarolina11.933.0105.9485.31613.62342.4245.1SouthDakota2.013.517.9155.7570.51704.4147.5Tennessee10.129.7145.8203.91259.71776.5314.0Texas13.333.8152.4208.21603.12988.7397.6Utah3.520.368.8147.31171.63004.6334.5Vermont1.415.930.8101.21348.22201.0265.2Virginia9.023.392.1165.7986.22521.2226.7Washington4.339.6106.2224.81605.63386.9360.3WestVirginia6.013.242.290.9597.41341.7163.3Wisconsin2.812.952.263.7846.92614.2220.7Wyoming5.421.939.7173.9811.62772.2282.0異？給出合理的解釋。計算從樣本相關(guān)矩陣動身計算的第一樣本主成分的得分并予以排序.2、從樣本相關(guān)矩陣動身，做因子分析。SAS【試驗方法與步驟】procprincompdata=work.crimeprocprincompdata=work.crimecovariance;run;樣本相關(guān)矩陣做主成分分析：procprocprincompdata=work.crime;run;對第一樣本主成分排序procprincompdata=crimeout=defen;runrun;procprocsortdata=defen;bybyprin1;runrun;16procprintdata=defen;run;2、程序：procfactordata=work.crimescore;run;【試驗結(jié)果】1718192021試驗四1991月平均收入的數(shù)據(jù)分析【試驗?zāi)康摹縎AS軟件對試驗數(shù)據(jù)進展判別分析和聚類分析，生疏數(shù)據(jù)分析方法，培育學(xué)生分析處理實際數(shù)據(jù)的綜合力量。【試驗內(nèi)容】1991年全國各省、區(qū)、市城鎮(zhèn)居民月平均收入狀況見下表，變量含義如下：X1-人均生活費收入〔元/人；X2-人均全民全部制職工工資〔元/人X3人均來源于全民標(biāo)準(zhǔn)工資〔/人X4人均集體全部制工資〔元/人X5〔元/人X6〔元/人X7-人均各種津貼〔/人X8職工人均從工作單位得到的其他收入〔/人X9-個體勞動者收入〔元/人。x1x2x1x2x3x4x5x6x7x8x9名型北京1170.03110.259.768.384.4926.816.4411.90.41天津1141.5582.5850.9813.49.3321.312.369.211.05河北1119.483.3353.39117.5217.311.79120.7上海1194.53107.860.2415.68.883121.0111.80.16山東1130.4686.2152.315.910.520.6112.149.610.47湖北1119.2985.4153.0213.18.4413.8716.478.380.51廣西1134.4698.6148.188.94.3421.4926.1213.64.56海南1143.7999.9745.66.31.5618.6729.4911.83.82四川1128.0574.9650.1313.99.6216.1410.1814.51021云南1127.4193.5450.5710.55.8719.4121.212.60.9疆1122.96101.469.76.33.8611.318.965.624.62山西2102.4971.7247.729.426.9613.127.96.660.61內(nèi)蒙古2106.1476.2746.199.656.279.65520.16.970.96吉林2104.9372.9944.613.79.019.43520.616.651.68黑龍江2103.3462.9942.9511.17.418.34210.196.452.68江西298.08969.4543.0411.47.9510.5916.57.691.08河南2104.1272.2347.319.486.4313.1410.438.31.11貴州2108.4980.7947.526.063.4213.6916.538.372.85陜西2113.9975.650.885.213.8612.949.4926.771.27甘肅2114.0684.3152.787.815.4410.8216.433.791.19青海2108.880.4150.457.274.078.37118.985.950.83寧夏2115.9688.2151.858.815.6313.9522.654.750.97遼寧3128.4668.9143.4122.415.313.8812.429.011.41江蘇3135.2473.1844.5423.915.222.389.66113.91.19浙江3162.5380.1145.9924.313.929.5410.913223.47安徽3安徽3111.7771.0743.6419.412.516.689.6987.020.63福建3139.0979.0944.1918.510.520.2316.477.673.08湖南312484.6644.0513.57.4719.1120.4910.31.76待廣東 211.311441.4433.211.248.7230.7714.911.1待西藏 175.93163.857.894.223.3717.8182.3215.70判判率作出估量。2〕進展Bayes判別，并用回代法與穿插確認法驗證判別結(jié)果。2、1〕用最短距離法、最長距離法與類平均法聚類，畫出譜系圖，并寫出分3類的結(jié)果；2〕3