DEGREE PREDICTION USING LOGISTIC REGRESSION
(2013) MASM01 20131Mathematical 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:
http://lup.lub.lu.se/studentpapers/record/3737416
 author
 Kidanekal, Hailegebriel and Assefa Belayhun, Endriyas
 supervisor

 Anna Lindgren ^{LU}
 organization
 course
 MASM01 20131
 year
 2013
 type
 H2  Master's Degree (Two Years)
 subject
 language
 English
 id
 3737416
 date added to LUP
 20130513 13:56:38
 date last changed
 20130513 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}, }