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DEGREE PREDICTION USING LOGISTIC REGRESSION

Kidanekal, Hailegebriel and Assefa Belayhun, Endriyas (2013) MASM01 20131
Mathematical Statistics
Abstract (Swedish)
To evaluate the efficiency of the previous years or to set visible plan in different aspects for the upcoming years in higher institutions studying students’ time to degree is important. Since logistic regression is a method used to predict a dependent categorical outcome or predict the probability of an event occurrence, studying Students’ time to degree using logistic regression is a reasonable way to predict the probability of students’ time to graduate considering influential factors that magnify and make a difference between different types of students. This difference can be the difference between age, gender, study programmes and so on. Thus, this study explores the prediction of degree at University of Lund Engineering faculty... (More)
To evaluate the efficiency of the previous years or to set visible plan in different aspects for the upcoming years in higher institutions studying students’ time to degree is important. Since logistic regression is a method used to predict a dependent categorical outcome or predict the probability of an event occurrence, studying Students’ time to degree using logistic regression is a reasonable way to predict the probability of students’ time to graduate considering influential factors that magnify and make a difference between different types of students. This difference can be the difference between age, gender, study programmes and so on. Thus, this study explores the prediction of degree at University of Lund Engineering faculty students on time and in the consecutive semesters based on significant factors. (Less)
Please use this url to cite or link to this publication:
author
Kidanekal, Hailegebriel and Assefa Belayhun, Endriyas
supervisor
organization
course
MASM01 20131
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
3737416
date added to LUP
2013-05-13 13:56:38
date last changed
2013-05-13 13:56:38
@misc{3737416,
  abstract     = {To evaluate the efficiency of the previous years or to set visible plan in different aspects for the upcoming years in higher institutions studying students’ time to degree is important. Since logistic regression is a method used to predict a dependent categorical outcome or predict the probability of an event occurrence, studying Students’ time to degree using logistic regression is a reasonable way to predict the probability of students’ time to graduate considering influential factors that magnify and make a difference between different types of students. This difference can be the difference between age, gender, study programmes and so on. Thus, this study explores the prediction of degree at University of Lund Engineering faculty students on time and in the consecutive semesters based on significant factors.},
  author       = {Kidanekal, Hailegebriel and Assefa Belayhun, Endriyas},
  language     = {eng},
  note         = {Student Paper},
  title        = {DEGREE PREDICTION USING LOGISTIC REGRESSION},
  year         = {2013},
}