Normal view MARC view ISBD view

Logistic regression analysis of the performance in Mathematics of CvSU-CAS freshmen students / by Mhay S. Esporlas.

By:

Esporlas, Mhay S [author]

Contributor(s):

Ballenas, Evelyn B [adviser]

Material type: Text

TextLanguage: English Publication details: Indang, Cavite : Cavite State University- Main Campus, 2013.Description: xvii, 181 pages : illustrations ; 28 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

Subject(s):

DDC classification:

519.536 Es6 2013

Online resources:

Click here to view thesis abstract and table of contents

Production credits:

College of Arts and Sciences (CAS)

Abstract: ESPORLAS, MHAY S. "Logistic Regression Analysis of the Performance in Mathematics of CvSU-CAS Freshmen Students". An Undergraduate Thesis. BS Applied Mathematics (with specialization in Statistics). Cavite State University, Indang. April 2011. Thesis Adviser. Mrs. Evelyn B. Ballenas. This study was conducted from October 2010 to March 2011 and aimed to determine the factors which affect the academic performance of Cavite State University (CvSU) freshmen students of the College of Arts and Sciences (CAS) and to predict the proportion that a student will pass or fail in Math 1 given the identified factors affecting their academic performance in Mathematics. The independent variable considered were: age, program, gender, schedule, address, civil status, study hours, religion, extracurricular activities, monthly family income, mother's occupation, father's occupation and type of secondary school where graduated. The derived Logistic Model was: Logit (Y) = -0.062 x age + 3.038 x type of school graduated + 0.057 x program The Logistic Regression Model showed that the independent variables age, type of secondary school where graduated and program highly affect the academic performance of CvSU-CAS freshmen students. Considering the classification rate of the model, it can be concluded that the Logistic Regression Model was really a better model representing the factors of the academic performance of CvSU-CAS freshmen students.

Average rating: 0.0 (0 votes)

Holdings ( 1 )
Title notes ( 5 )

Holdings
Item type	Current library	Collection	Call number	Materials specified	URL	Status	Notes	Date due	Barcode
Theses / Manuscripts	Ladislao N. Diwa Memorial Library Theses Section	Non-fiction	519.536 Es6 2013 (Browse shelf(Opens below))		Link to resource	Room use only	T-5195		00000140

Theses (BS Applied Mathematics Major in Statistics) Cavite State University.

Includes bibliographical references.

College of Arts and Sciences (CAS)

ESPORLAS, MHAY S. "Logistic Regression Analysis of the Performance in Mathematics of CvSU-CAS Freshmen Students". An Undergraduate Thesis. BS Applied Mathematics (with specialization in Statistics). Cavite State University, Indang. April 2011. Thesis Adviser. Mrs. Evelyn B. Ballenas.
This study was conducted from October 2010 to March 2011 and aimed to determine the factors which affect the academic performance of Cavite State University (CvSU) freshmen students of the College of Arts and Sciences (CAS) and to predict the proportion that a student will pass or fail in Math 1 given the identified factors affecting their academic performance in Mathematics. The independent variable considered were: age, program, gender, schedule, address, civil status, study hours, religion, extracurricular activities, monthly family income, mother's occupation, father's occupation and type of secondary school where graduated. The derived Logistic Model was: Logit (Y) = -0.062 x age + 3.038 x type of school graduated + 0.057 x program The Logistic Regression Model showed that the independent variables age, type of secondary school where graduated and program highly affect the academic performance of CvSU-CAS freshmen students.
Considering the classification rate of the model, it can be concluded that the Logistic Regression Model was really a better model representing the factors of the academic performance of CvSU-CAS freshmen students.

April 07, 2014 T-5195 Submitted to the University Library