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Descriminant and logistic regression analyses on the evaluation of CvSU-CAS graduates from 2001 to 2004 / Mildred F. Arellano, Sheila Marie G. Villa and Janice M. Nuestro.

By:

Arellano, Mildred F [author]

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Material type: Text

TextLanguage: English Publication details: Indang, Cavite : 2005. Cavite State University- Main Campus,Description: xxii, 73 pages : illustrations ; 28 cmContent type:

text

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unmediated

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volume

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DDC classification:

519.5 Ar3 2005

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College of Arts and Science (CAS)

Abstract: ARELLANO, MILDRED FELIX; VILLA, SHIELA MARIE GULPO and NUESTRO, JANICE MO,JICA, "Discriminant and Logistic Regression Analyses on the Evaluation of Employment Status Among CvSU-CAS Graduates from 2001 to 2004", A Special Problem, Bachelor of Science in Applied Mathematics (Major in Statistics), Cavite State University, Indang, Cavite, March 2005, Anna Marie A. Ardina. The study was conducted to: (l) present the profile of CvSU-CAS graduates from 2001 to 2004 with respect to their employment status; (2) identify the factors affecting their employment status; and (3) formulate discriminant and logistic regression models for the employment status. The independent variables considered were age, gender, height, weight, civil status, parents' education and income, grade point average, field of specialization, number of years stayed in CVSIJ, year graduated, eligibilities and work experience. The derived Fisher's linear discriminant functions for group were: ho -8.789 + 2.619x Course + 3 262 XCS + 2.908 x GPA + 2.554 x FS hi - -12.120 + 3.656 x Course + 1.103 X CS + 2.173 xGPA + 3.997xFS The discriminant functions showed that the graduates' course, civil status, GPA, and field of specialization affected their employment status The derived logistic regression estimate was logit (Y) 25 097 3.186 x course(AM) - 1 224 x means - 0337 x Height + 2 729 x CS (1) + 10 269 x FS (R) The logistic regression model showed that the course, means of application, height, civil status, and field of specialization affect the graduates' employment status. Considering the classification rates of each model, it can be concluded that the logistic regression model was the better model representing the factors of employability since it gave a higher classification rate than the discriminant function

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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	519.5 Ar3 2005 (Browse shelf(Opens below))		Link to resource	Room use only	SP-3000		00004267

Special Problem (BS Applied Mathematics - - Statistics) Cavite State University.

Includes bibliographical references.

College of Arts and Science (CAS)

ARELLANO, MILDRED FELIX; VILLA, SHIELA MARIE GULPO and
NUESTRO, JANICE MO,JICA, "Discriminant and Logistic Regression Analyses on the Evaluation of Employment Status Among CvSU-CAS Graduates from 2001 to 2004", A Special Problem, Bachelor of Science in Applied Mathematics (Major in Statistics), Cavite State University, Indang, Cavite, March 2005, Anna Marie A. Ardina.
The study was conducted to: (l) present the profile of CvSU-CAS graduates from 2001 to 2004 with respect to their employment status; (2) identify the factors affecting their employment status; and (3) formulate discriminant and logistic regression models for the employment status. The independent variables considered were age, gender, height, weight, civil status, parents' education and income, grade point average, field of specialization, number of years stayed in CVSIJ, year graduated, eligibilities and work experience.
The derived Fisher's linear discriminant functions for group were:
ho -8.789 + 2.619x Course + 3 262 XCS + 2.908 x GPA + 2.554 x FS hi - -12.120 + 3.656 x Course + 1.103 X CS + 2.173 xGPA + 3.997xFS
The discriminant functions showed that the graduates' course, civil status, GPA, and field of specialization affected their employment status
The derived logistic regression estimate was
logit (Y) 25 097 3.186 x course(AM) - 1 224 x means - 0337 x
Height + 2 729 x CS (1) + 10 269 x FS (R)
The logistic regression model showed that the course, means of application, height, civil status, and field of specialization affect the graduates' employment status.
Considering the classification rates of each model, it can be concluded that the logistic regression model was the better model representing the factors of employability since it gave a higher classification rate than the discriminant function

Submitted to the University Library 04/14/2005 SP-3000