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1、.Graduates to apply for the quantitative analysis of changes in number of graduate students一Topics raisedIn this paper, the total number of students from graduate students multivariate analysis specific analysis, and collect relevant data, model building, this quantitative analysis. The number of re
2、lations between the school the total number of graduate students with the major factors, according to the size of the various factors in the coefficient in the model equations, analyze the importance of various factors, exactly what factors in changes in the number of graduate students aspects play
3、a key role in and changes in the trend for future graduate students to our proposal.The main factors affect changes in the total number of graduate students for students are as follows：Per capita GDP - which is affecting an important factor to the total number of students in the graduate students Th
4、e total population - it will affect the total number of students in graduate students is an important factor The number of unemployed persons - this is the impact of a direct factor of the total number of students in the graduate students Number of colleges and universities - which is to influence p
5、recisely because of the emergence of more institutions of higher learning in the school the total number of graduate students is not a small factor 二 Establish ModelY=+1X1+2X2+3X3+4X4 +uAmong them, theY-in the total number of graduate students X1 - per capita GDP X2 - the total population X3 - the n
6、umber of unemployed persons X4 - the number of colleges and universities 三、Data collection1. date ExplainHere, using the same area time-series data were fitted2. Data collectionTime series data from 1986 to 2005, the specific circumstances are shown in Table 1Table 1：YX1X2X3X41986110371963107507264.
7、4105419871201911112109300276.6106319881127761366111026296.2107519891013391519112704377.910751990930181644114333383.210751991881281893115823352.210751992941642311117171363.9105319931067712998118517420.1106519941279354044119850476.4108019951454435046121121519.6105419961633225846122389552.8103219971763
8、536420123626576.81020199819888567961247615711022199923351371591257865751071200030123978581267435951041200139325686221276276811225200250098093981284537701396200365126010542129227800155220048198961233612998882717312005978610140401307568391792四、Model parameter estimation, inspection and correction1. Mo
9、del parameter estimation and its economic significance, statistical inference testtwowaytwowaytwowaygraph twoway lfit y X1graph twoway lfit y X2graph twoway lfit y X3graph twoway lfit y X4Y = 59.22454816*X1- 7.158602346*X2- 366.8774279*X3+621.3347694*X4 6.3522883.257541157.940246.72256 t= 9.323341-2
10、.197548-2.32288913.29839+ 270775.151369252.80.733306R2=0.996048 Adjusted R-squared=0.994994F=945.1415 DW=1.596173Visible, X1, X2, X3, X4 t values are significant, indicating that the per capita GDP, the total population of registered urban unemployed population, the number of colleges and universiti
11、es are the main factors affecting the total number of graduate students in school.Model coefficient of determination for 0.996048 amendments coefficient of determination of 0.994994, was relatively large, indicating high degree of model fit, while the F value of 945.1415, indicating that the model o
12、verall is significant。In addition, the coefficient of X1, X4, in line with economic significance, but the coefficient of X2, X3, does not meet the economic significance, because from an economic sense, with the increase in the total population , the total number of graduate students should be increa
13、sed, and due to the increase in the number of unemployed, there will be more and more people choose graduate school, so that the total number of unemployed and graduate students should be positively correlated. X2, X3 coefficient sign contrary to expectations, which may indicate the existence of severe multicollinearity. 2.计量经济学检验The above table can be seen to explain the positive correlation between the height of the variable X1 and X2, X3, X4, X2, X1, X3, between the highly positively correlated, showing that
