The data above clearly indicates a high correlation between total funding level and university ranking. Top universities enjoy abundant government grants as well as private investment, enabling them to invest in infrastructure, staff, and equipment, which all enhance their competitiveness. Regional universities, however, have much less funding – ¥4.7bn for Northeastern University is merely 20% of the ¥23.3bn available to Tsinghua University. Liaoning University, with even lower funding at ¥2.2bn, unsurprisingly ranks lower than those with higher funding. From top universities to Northeastern University to Liaoning University, we see a clear trend that the lower the funding level, the lower the ranking is. Analyzing the correlation coefficient between Ranking and Funding, the coefficient is 77%, confirming how closely related funding is to the ranking of a university.In addition to government funding, other factors also affect a university’s income. Highly ranked universities receive additional resources as enterprise grants, which are grants obtained from private companies/organizations to research on their behalf. The value of enterprise grants received by Tsinghua University is 3.4 times that of Northeastern University, which is then 53 times that of Liaoning University. Being able to obtain enterprise grants means that more research can be conducted, highly skilled teaching staff will be attracted to the university, and more public funding can be redirected to improving education instead of spending in research. Liaoning University performed very poorly in this area and increasing its enterprise grants by building active relationships with industries will help it boost its funding and raise its profile. This is partly explained by its much lower volume of scientific journal publications, which indicates that its ability to conduct research may not be as attractive as that of Northeastern University. The correlation coefficient between enterprise grants from analyzing 310 universities in China is 54%, indicating that these two factors are closely correlated.