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首页> 外文学位 >FEASIBILITY OF COLLEGE STUDENT PLACEMENT AT KING ABDULAZIZ UNIVERSITY BY DISCRIMINANT FUNCTION AND MULTIPLE REGRESSION ANALYSIS.
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FEASIBILITY OF COLLEGE STUDENT PLACEMENT AT KING ABDULAZIZ UNIVERSITY BY DISCRIMINANT FUNCTION AND MULTIPLE REGRESSION ANALYSIS.

机译：判别函数和多元回归分析法在阿卜杜拉齐兹国王大学进行学生安置的可行性。

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摘要

Purpose. This study was designed to answer two research questions: (1) How can we determine which college of study a beginning student with a given set of academic characteristics should enter? and (2) Can we predict the GPA in a given college of study and determine the variables which contribute most to the prediction of the student's success in terms of GPA?;Discriminant function was used to answer the first research question and regression analysis was used to answer the second question. Six subjects from the high school record were used as the classification variables in discriminant analysis and as the predictor variables to predict the college GPA in regression analysis.;Findings. (1) The discriminant function correctly classified students to each of the six scientific colleges at King Abdulaziz University as follows: Science-59%; Engineering-79%; Medicine-85%; Earth Sciences-70%; Marine Sciences-81%; Meteorology-88%. The overall correct classification was 77%. (2) The variables which contributed most to the prediction of success in the scientific colleges at King Abdulaziz University in terms of the GPA were English, science, math, and total score.;Conclusions. The following major conclusions were drawn from the results of this study. (1) Multiple discriminant analysis can be effectively used to classify a high school graduate into an area of study where he will be most likely to succeed. (2) Multiple regression analysis can be effectively used to: (a) predict the success of the student in terms of the GPA to be expected and (b) identify the variable which contributes most to the prediction. (3) Using a combination of both statistical techniques--multiple discriminant analysis and multiple regression analysis--will give better prediction and accurate classification than using one alone.;Procedure. Subjects of this study were limited to male students who had satisfactory standing at the senior year level in the six scientific colleges of King Abdulaziz University in spring 1981. A total of 236 students comprised the sample for the study. The data used were collected from student files in the registrar's office at King Abdulaziz University.
机译：目的。该研究旨在回答两个研究问题：（1）我们如何确定具有给定学业特征的初学者应进入哪个学习学院？ （2）我们能否在给定的大学中预测GPA并确定对GPA预测学生成功最重要的变量？；使用判别函数回答第一个研究问题，并使用回归分析回答第二个问题。高中记录的六个主题用作判别分析中的分类变量，并作为回归分析中预测大学GPA的预测变量。 （1）判别函数将学生正确地分类为阿卜杜勒阿齐兹国王大学六所科学学院的学生，如下：理科-59％；工程-79％；医药85％;地球科学-70％；海洋科学-81％；气象：88％。总体正确的分类是77％。 （2）英语，科学，数学和总分方面，对阿卜杜勒阿齐兹国王大学科学学院的成功预测最重要的变量是英语，科学，数学和总分。从这项研究的结果得出以下主要结论。 （1）可以使用多重判别分析将高中毕业生分类为最有可能成功的学习领域。 （2）多元回归分析可以有效地用于：（a）根据预期的GPA预测学生的成功，以及（b）确定对预测贡献最大的变量。 （3）与单独使用一种统计技术相结合-多重判别分析和多元回归分析-将提供更好的预测和准确的分类。这项研究的对象仅限于在1981年春季在阿卜杜勒阿齐兹国王大学（King Abdulaziz University）的六所科学学院中取得较高年级成绩的男学生。该研究的样本共有236名学生。所使用的数据是从阿卜杜勒阿齐兹国王大学注册处的学生档案中收集的。

著录项

  • 作者

    ALHARBEY, ABDULLAH HUMUD.;

  • 作者单位

    University of Northern Colorado.;

  • 授予单位 University of Northern Colorado.;
  • 学科 Statistics.
  • 学位 Ph.D.
  • 年度 1982
  • 页码 125 p.
  • 总页数 125
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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