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Statistical Analysis Model Of Hierarchical Training Of University Students

Posted on:2014-11-06Degree:MasterType:Thesis
Country:ChinaCandidate:Y X YuanFull Text:PDF
GTID:2267330392472258Subject:Applied statistics
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Graduation whereabouts of college students is the problem that students and thecommunity concern.The graduation whereabouts and the training quality of thegraduated students colleges and universities are closely related,and the employmentsituation plays an important instructive role in the training programs and teachingquality. According to the employment status of students majoring in mathematics at auniversity in Chongqing as an example, the paper contact the results of students and theemployment situation together, to obtain the corresponding classification of studentsaccording to their results and characteristic of learning achievement for each type ofstudents. Then establish the mapping relationship between students’ characteristics andtypes of employment, and the school can adjusted settings of course, arrangement ofnumber hours,reform of teaching contents and improvement of teaching methodaccording to the status of students and the demand of social, then school can build adynamic system of hierarchical training of students in various forms, to get a Rationalallocation of education resources. Pay attention to guide students to develop toward thedirection of their advantages, make excellent talents better and faster growth, achievethe menu type training mode, increase flexibility of the training mode of highereducation.This paper presents a model of hierarchical training of college students based onmultivariate statistical analysis. According to the the employment situation ofstudents,as the index to their achievement, using hierarchical clustering method, thestudents are divided into three categories (graduate students, students that obtainemployment and unemployed),then obtain the feature of the three categories of students:The first class (graduate class): they have obvious advantages in professionalfoundation courses and public foundation courses, this part of the students ask theteachers’ ability of raising questions and inspiring students to think in the teaching. Themain is to cultivate their creative thinking, to train them to be innovative talents withvery competitive advantage.Second (employment class): this kind of student’s are the practical talents thatsocial needed. This part of the students ask the school to pay attention to the cultivationof practice ability and the training of application and innovational ability,to make students have a wide range of knowledge, rational knowledge structure and the abilityof solving the real problems for the society.Third types of (unemployment class): the characteristics of this part of the studentsshow that: the poor foundation, make-up more subjects, wasting a lot of time in theuniversity stage, having courses do not pass at the time of graduation, resulting indifficult employment. This part of the students ask the school needs to pay moreattention, and complete the conversion of poor students as soon as possible, to avoidthis kind of students.This paper have also done regression analysis for the first class on the clusteringresults according to the postgraduate entrance scores and records of studies inundergraduate, then screen of the variables to do factor analysis of the selected variables,final determine the training program in teaching of graduate students; regressionanalysis for the first class on the clustering results according to the postgraduateentrance scores and records of studies in undergraduate though the regression analysisfor the second groups of students according to their undergraduate grades andemployment status,it can be fond that the relationship between achievements andemployment is not obvious, but other factors, such as communicative ability, practicalability and so on, can not be ignored,this part of the students should also strengthenthe comprehensive quality education.
Keywords/Search Tags:Colleges and universities student achievement scores, managementmethods of multivariate statistical, clustering regression analysis, factoranalysis
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