Statistical Analysis On The University Students’ Grades And The College Entrance Examination’ Grades

Undergraduate education, as an important part of higher education, plays airreplaceable role in enhancing people’s quality and training professional talents,and these thousands of talents make a great contribution to construction of ourcountry and socialist modernization construction. However, College EntranceExamination, a significant route from high school to college, suffers fromcontroversy.In the era of College Entrance Examination being paid attention to byeveryone, College Entrance Examination serves as a stepping stone to highereducation or has a profound influence on university students’ grade, which is also afocus. It follows that evaluation of education appears with higher education and alot of educators evaluate quantitatively and qualitatively from the grade of CollegeEntrance Examination, university students’ grades, comprehensive quality ofcollege students, development after graduating and so on. In addition, we state theeffect of the grade of College Entrance Examination to development after studentsreceiving higher education and other problems.In this paper, with the help of relative statistical methods, statistical analysison the university students’ grades(USG) and the College Entrance Examination’Grades(CEEG) are made in School of Mechanical and Automotive Engineering inHefei University of Technology. The research results indicate that there is muchcorrelation between CEEG and USG. On the same time, this correlation coefficientvaries from major to major. In addition, statistical regression models among someof representative courses, the CEEG and the grade of courses are constructed.Found that USG and CEEG, the grade of courses are linearly related. Also,discussion on the professional differences, USG differences characteristics ofuniversity learning and some factors likes Course difficulty, Study habits whichhave an influence on university Students’ Grades are made.At the same time, we also study the large sample statistical properties of thelocation parameter change point estimator, such as the strong consistency andconvergence rate.