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# 基于SAS对第三产业增加值的因子分析

2.因子分析 过程： 2.因子分析 SAS 过程： data a; input district \$ x cards; x1 x2 x3 x4 x5 x6;

1978 872.5 1979 878.9 1980 982.0 1981 1076.6 1982 1163.0 1983 1338.1 1984 1786.3 1985 2585.0 1986 2993.8 1987 3574.0 1988 4590.3 1989 5448.4 1990 5888.4 1991 7337.1 1992 9357.4 1993 11915.7 1994 16179.8 1995 19978.5 1996 23326.2 1997 26988.1 1998 30580.5 1999 33873.4

182.0 193.7 213.4 220.7 246.9 274.9 338.5 421.7 498.8 568.3 685.7 812.7 1167.0 1420.3 1689.0 2174.0 2787.9 3244.3 3782.2 4148.6 4660.9 5175.2

242.3 200.9 193.8 231.1 171.4 198.7 363.5 802.4 852.6

44.6 44.0 47.4 54.1 62.3 72.5 96.8

68.2 66.9 75.0 79.8 114.8 149.0 203.9

79.9 86.3 96.4 99.9 110.8 121.8 162.3 215.2 298.1 382.6 473.8 566.2

255.6 287.1 356.0 390.9 456.8 521.2 621.2 747.5 824.6 926.3 1120.6 1291.6 1470.9 1819.9 2271.3 3163.7 4465.8 5602.9 6778.3 8423.0 10087.3 11767.7

138.3 259.9 163.2 356.4

1059.6 187.1 450.0 1483.4 241.4 585.4 1536.2 277.4 964.3

1268.9 301.9 1017.5 662.2 1834.6 442.3 1056.3 763.7 2405.0 584.6 1306.2 1101.3 2816.6 712.1 1669.7 1379.6 3773.4 1008.5 2234.8 1909.3 4778.6 1200.1 2798.5 2354.0 5599.7 1336.8 3211.7 2617.6 6327.4 1561.3 3606.8 2921.1 6913.2 1786.9 3697.7 3434.5 7491.1 1941.2 3816.5 3681.8

2000 38714.0 2001 44361.6 2002 49898.9 2003 56004.7 2004 64561.3 2005 74919.3 2006 88554.9

6161.0 6870.3 7492.9 7913.2 9304.4

8158.6 2146.3 4086.7 4149.1 9119.4 2400.1 4353.5 4715.1 9995.4 2724.8 4612.8 5346.4 11169.5 3126.1 4989.4 6172.7 12453.8 3664.8 5393.0 7174.1

14012.4 16903.3 19726.7 22633.9 26571.2

10666.2 13966.2 4195.7 6086.8 8516.4 31488.0 12183.0 16530.7 4792.6 8099.1 10370.5 36579.1

2007 111351.9 14601.0 20937.8 5548.1 12337.5 13809.7 44117.7 2008 131340.0 16362.5 26182.3 6616.1 14863.3 14738.7 52577.1 2009 148038.0 16727.1 28984.5 7118.2 17767.5 18654.9 58785.9 2010 173087.0 18968.5 35746.1 8068.5 20980.6 22315.6 67007.8 ; proc factor data=a n=2;run; proc factor data=a n=2 rotate=varimax score out=scoreout;; var x1-x6; run; proc sort data=scoreout out=f1; by descending factor1; proc sort data=scoreout out=f2; by descending factor2; run; proc print data=scoreout;run;

SAS based on the tertiary industry added value factor analysis Calculation of B092 lining
Abstract: the tertiary industry is a country the main component in national economy, in the developed countries, the tertiary industry accounted for the proportion of the national economy is very large. There are many factors that influence the tertiary industry, according to the China Statistical Yearbook 2011 as the data source, through the SAS software research wholesale and retail trade, accommodation and catering industry, financial industry and the tertiary industry added value influence factors.

Keywords: the tertiary industry SAS

factor analysis

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