统计分析软件复习题答案.docx
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统计分析软件复习题答案.docx
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统计分析软件复习题答案
习题程序:
1.
dataSCORE;
inputname$sex$ChinesemathsphysicschemistEnglish;
sum=Chinese+maths+physics+chemist+English;
mean=sum/5;
cards;
王辉男8085827890
李唱女8593887089
张三男7786678285
王二女8178938387
;run;
datajinrong;
SetSCORE;
Wheremaths>85;
Run;
2.
inputxr;
doi=1to3;
x+x*r;
end;
cards;
5000.07
;run;
3.
(1)dataincome;inputyearx1-x3;
income=x1+x2+x3;dropx1x2x3;
cards;
1985298.2829.4739.95
1990510.8670.6875.81
1995996.51287.24195.74
20001125.34488.89515.35
20011165.17532.61533.80
;run;
(2)dataincome(keep=yearincome);
inputyearx1-x3;income=x1+x2+x3;
cards;
1985298.2829.4739.95
1990510.8670.6875.81
1995996.51287.24195.74
20001125.34488.89515.35
20011165.17532.61533.80
;run;
(3)dataincome(drop=i);
inputx1-x3;
arrayconsum{3}x1-x3;
doi=1to3;
sum+consum(i);
end;
cards;
1985298.2829.4739.95
1990510.8670.6875.81
1995996.51287.24195.74
20001125.34488.89515.35
20011165.17532.61533.80
;run;
4.
datagroup1group2;
inputregion$income@@;
ifincome>=2366.40thendo;
outputgroup1;
n+1;
end;
elsedo;outputgroup2;
m+1;
end;
cards;
beijing5025.5tianjin3947.72hebei2603.6shanxi1956.05
nemenggu1973.37liaoning2557.93jilin2182.22heilong2280.28shanghai5870.87jiangsu3784.71zhejiang4582.34anhui2020.04fujian3380.72jiangxi2231.6shandong2804.51henan2097.86hubei2352.16hunanÏ2299.46guangdong3769.79guangxi1944.33
hainan2226.47chongqing1971.18sichuan1986.99guizhou1411.73yunnan1533.74xizang1404.01shananxi1490.8gansu1508.61
qinghai1557.32ningxia1823.05xinjiang1710.44
;
procprintdata=group1(drop=m);
title'group1';
procprintdata=group2(drop=n);
title'group2';run;
5.
dataa;
inputregion$wage@@;
ifwage<10000thendelete;
cards;
beijing19776tianjin15110hebei9139shanxi8618neimenggu8737
liaoning10609jilin9043heilongjiang8924shanghai21961jiangsu12917
zhejiang19514anhui8501fujian13313jiangxi8346shandong11067
henan8573hubei9133hunan9991guangdong16779guangxi9209hainan8102chongqing10035sichuan10783guizhou9308yunnan10880xizang20112shananxi9440gansu10442qinghai14028ningxia11112xinjiang10145
;run;
6.
datanongye;
inputxiangmu$year85year90year95year00year01;
cards;
gulei21111
roulei21111
mianhua11111
dadou33344
;
datagongye;
inputxiangmu$year85year90year95year99year00;
cards;
gang44211
mei21111
yuanyou65555
;
dataorder;setnongyegongye;procprint;run;
7.
datagdp;inputgdp1-gdp45@@;
cards;
144150165168200216218185173181208240254235222243275288292309310327316339379417460489525580692853956110413551512163418792287293939234854557660536392
;procmeansdata=gdpmeanstdcvskewnesskurtosis
;run;
8.
datagdp;inputarea$gdpconsumptcapitalexport@@;
cards;
beijing2845.651467.711775.3-397.36
tianjin1840.1901.85934.483.77
hebei5577.782509.32511.57556.91
shanxi1787.761046.43800.27-58.94
neimenggu1545.326789936.1894062614.1373826-5
liaoning5033.082828.091625.5579.49
jilin2087.871331.32790.99-34.44
heilongjiang3515.699822110.541130.53982274.62
shanghai4950.842149.072294.46507.31
jiangsu9403.34295.964239.17868.17
zhejiang6749.183306.12891.02552.06
anhui3290.1304142108.094751185.495664-3.46
fujian4218.312225.231939.6153.47
jiangxi2161.751357.47800.833.45
shangdong9438.314582.614513.32342.38
henan5640.113114.132329.32196.66
hubei4557.022408.841963.46184.72
hunan39832553.141426.473.39
gongdong10647.715841.323860.81945.58
guangxi2231.191597.05769.04-134.9
hainan546.62299.86254.79-8.03
chongqing1769.771078.06819.08-127.37
sichuan4421.762691.471726.333.96
guizhou1084.9833.87599.95-348.92
yunnan2074.711430.44929.73-285.46
xizang138.3182.7949.725.8
shananxi1844.271004.5972.51-132.74
gansu1081.51674.42444.89-37.8
qinghai294.83197.79207.39-110.35
ningxia298.38223.52207.69-132.83
xinjiang1485.48854.6771.42-140.54
;
procsort;bygdp;
proctransposeout=trans;
idarea;
vargdpconsumptcapitalexport;
procmeanssum;
vargdpconsumptcapitalexport;
procmeansmeanmaxminstdcvskewnesskurtosisclm;run;
9.
dataa;
inputr@@;
cards;
718525.4723715.3702236.637390.56632662.2443082.759706.7
17774.8115653558135.41581666513099.3213847.4291708030368.26104925232864.331972.76364228.640924.8530557.3439874.4632741.52248281.198826.12195651443551.33387256.167158.48238265.750744.4751291.2454995.52157951.540349.33220848.318309.9920264.1331359.9941325.3349634.9551689.58129214.635857.5627680.2158609.6224192.6915665.4660003.253617.028605.7885371.95161167.124852.0348598.5836004.8113104668424.8463149.74
;
procmeansmeanmaxminmaxdec=2varstdcvskewnesskurtosisalpha=0.1clmnnmissrange;run;
10.
dataa(drop=i);
doi=1to100by1;
x=normal(0);
y=100+sqrt(30)*x;output;end;
procmeansalpha=0.05clm;run;
procunivariatedata=anormal;run;
11.
dataa;inputb@@;
cards;
167.939169.369176.228172.077163.284169.564174.022
157.814170.794164.796172.887166.425166.189176.456
162.080167.290175.004165.762158.315167.812178.715
170.624173.090180.698172.621176.095164.211174.641
173.427171.869166.742167.137175.704168.537175.321
173.532168.285171.333173.911171.226174.694169.868
178.338171.044178.550173.199168.664169.562168.996
;procunivariateplot;run;
12.
dataa;
inputyearr1r2r3r4r5r6r7@@;
cards;
192611.60.287.377.775.383.27-1.49
192737.4922.17.448.934.523.12-2.08
192843.6139.692.840.10.923.56-0.97
1929-8.42-51.363.273.426.014.750.2
1930-24.9-38.157.984.666.722.41-6.03
1931-43.34-49.75-1.85-5.31-2.321.07-9.52
1932-8.19-5.3910.8216.848.810.96-10.3
193353.99142.8710.38-0.071.830.30.51
1934-1.4424.2213.8410.0390.162.03
193547.6740.199.614.987.010.172.99
193633.9264.86.747.523.060.181.21
1937-35.03-58.012.750.231.560.313.10
193831.1232.86.135.536.23-0.02-2.78
1939-0.410.353.975.944.520.02-0.48
1940-9.78-5.163.396.092.9600.96
1941-11.59-92.730.930.50.069.72
194220.344.512.63.221.940.279.29
194325.988.372.832.082.810.353.16
194419.7553.724.732.811.80.332.11
194536.4473.614.0810.732.220.332.25
1946-8.07-11.631.72-0.110.3518.16
19475.710.92-2.34-2.620.910.59.01
19485.5-2.114.143.41.850.812.71
194918.7919.753.316.452.321.10-1.80
195031.7138.752.120.060.71.25.79
195124.027.8-2.69-3.930.361.495.87
195218.373.033.521.161.631.660.88
1953-0.99-6.493.413.643.231.820.62
195452.6260.585.397.192.680.86-0.5
195531.5620.440.48-1.29-0.651.570.37
19566.564.28-6.81-5.59-0.422.462.86
1957-10.78-14.578.717.467.843.143.02
195843.3664.89-2.22-6.09-1.291.541.76
195911.9616.4-0.97-2.26-0.392.951.5
19600.47-3.299.0713.7811.762.661.48
196126.8932.094.820.971.852.130.67
1962-8.73-11.97.956.895.562.731.22
196322.823.572.191.211.643.121.65
196416.4823.524.773.514.043.541.19
196512.4541.75-0.460.711.023.931.92
1966-10.06-7.010.23.654.694.763.35
196723.9883.57-4.95-9.181.014.213.04
196811.0635.972.57-0.264.545.214.72
1969-8.5-25.05-8.09-5.07-0.746.586.11
19704.01-17.4318.3712.1116.866.525.49
197114.3116.511.0113.238.724.393.36
197218.984.437.265.695.163.843.41
1973-14.66-30.91.14-1.114.616.938.8
1974-26.47-19.95-3.064.355.69812.20
197537.252.8214.649.27.835.87.01
197623.8457.3818.6516.7512.875.084.81
1977-7.1825.381.71-0.691.415.126.77
19786.5623.46-0.07-1.183.497.189.03
197918.4443.46-4.18-1.234.0910.3813.31
198032.4239.88-2.76-3.953.9111.2412.4
1981-4.9113.88-1.241.869.4514.718.94
198221.4128.0142.5640.3629.110.543.87
198322.5139.676.260.657.418.83.8
19846.27-6.6716.8615.4814.029.853.95
198532.1624.6630.0930.9720.337.723.77
198618.476.8519.8524.5315.146.161.13
19875.23-9.3-0.27-2.712.95.474.41
198816.8122.8710.79.676.16.354.42
198931.4910.1816.2318.1113.298.374.65
1990-3.17-21.566.786.189.737.816.11
199130.5544.6319.8919.315.465.63.06
19927.6723.359.398.057.193.512.9
19939.9920.9813.1918.2411.242.94.75
19941.313.11-5.76-7.77-5.143.92.67
199537.4334.4627.231.6716.85.62.54
199623.0717.621.4-0.832.15.213.32
199733.3622.7812.9515.858.385.261.7
;
procunivariatenormal;run;
13.
datagdp;
inputarea$gdpconsumptcapitalexport@@;
cards;
beijing2845.651467.711775.3-397.36
tianjin1840.1901.85934.483.77
hebei5577.782509.32511.57556.91
shanxi1787.761046.43800.27-58.94
neimenggu1545.326789936.1894062614.1373826-5
liaoning5033.082828.091625.5579.49
jilin2087.871331.32790.99-34.44
heilongjiang3515.699822110.541130.53982274.62
shanghai4950.842149.072294.46507.31
jiangsu9403.34295.964239.17868.17
zhejiang6749.183306.12891.02552.06
anhui3290.1304142108.094751185.495664-3.46
fujian4218.312225.231939.6153.47
jiangxi2161.751357.47800.833.45
shangdong9438.314582.614513.32342.38
henan5640.113114.132329.32196.66
hubei4557.022408.841963.46184.72
hunan39832553.141426.473.39
gongdong10647.715841.323860.81945.58
guangxi2231.191597.05769.04-134.9
hainan546.62299.86254.79-8.03
chongqing1769.771078.06819.08-127.37
sichuan4421.762691.471726.333.96
guizhou1084.9833.87599.95-348.92
yunnan2074.711430.44929.73-285.46
xizang138.3182.7949
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