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/student-papers/record/3737416
- author
- Kidanekal, Hailegebriel and Assefa Belayhun, Endriyas
- supervisor
- organization
- course
- MASM01 20131
- year
- 2013
- 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}}, }