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Discriminant and logistic analyses in classifying Cavite State University (CvSU) entrance examinees for degree courses with board examinations of SY 2006 - 2007 by Luisa B. Baes

By:

Baes, Luisa B [author]

Contributor(s):

Legaspi, Gemma S [adviser]

Material type: Text

TextLanguage: English Publication details: Indang, Cavite : 2007. Cavite State University- Main Campus,Description: xiii, 81 pages : illustrations ; 28 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

Subject(s):

DDC classification:

519.53 B14 2007

Online resources:

Click here to view thesis abstract and table of contents

Production credits:

College of Arts and Science (CAS)

Abstract: BAES, LUISA BREGUERA, "Discriminant and Logistic Regression Analyses in Classifying Cavite State University (CvSU) Entrance Examinees for Degree Courses with Board Examination of SY.2006-2007, A special problem, Bachelor of Science in Applied Mathematics ( Major in Statistics), Cavite State University, Indang, Cavite, Adviser: Gemma S. Legaspi. The study was conducted to: (1) determine the variables that may be used in developing the discriminant function used in classifying CvSU entrance examinees for degree courses with board examination; (2) develop an alternative model of accepting or rejecting incoming freshmen who intend to enrol in degree courses with board examination; and (3) compare the models derived from Linear Discriminant Analysis and Logit Analysis in terms of accuracy. The placement examinations of the CvSU degree courses with board examination of freshmen students in the first semester of SY 2006-2007 were used. The concept of proportional allocation under the stratified random sampling was used in drawing 756 examinees from a total of 1334 applicants who took the examination. The independent variables were gender, type of school, mathematical and verbal ability test The Fisher's Linear Discriminant Functions for two groups were: h0= a0+a1X1+a2X2+...akXk (not admitted group) h1= b0+b1X1+b2X2+...bkXk (admitted group). The derived Fisher's linear discriminant functions for the two groups were: h0 = -3.976 + 9.489 E -2 x score (not admitted) hi = -7.917 + 0.141 x score (admitted) The resulting logistic regression model was: Logit (V) = -1.297 + 0.053 x score The logistic regression model showed that the score in mathematical and verbal ability test affected the examinees in the examination status. The discriminant model was the better model representing the factors of the examination since it gave a higher classification rate than the discriminant function.

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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	519.53 B14 2007 (Browse shelf(Opens below))		Link to resource	Room use only	SP-3491		00007230

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

Includes bibliographical references.

College of Arts and Science (CAS)

BAES, LUISA BREGUERA, "Discriminant and Logistic Regression Analyses in Classifying Cavite State University (CvSU) Entrance Examinees for Degree Courses with Board Examination of SY.2006-2007, A special problem, Bachelor of Science in Applied Mathematics ( Major in Statistics), Cavite State University, Indang, Cavite, Adviser: Gemma S. Legaspi.
The study was conducted to: (1) determine the variables that may be used in developing the discriminant function used in classifying CvSU entrance examinees for degree courses with board examination; (2) develop an alternative model of accepting or rejecting incoming freshmen who intend to enrol in degree courses with board examination; and (3) compare the models derived from Linear Discriminant Analysis and Logit Analysis in terms of accuracy. The placement examinations of the CvSU degree courses with board examination of freshmen students in the first semester of SY 2006-2007 were used. The concept of proportional allocation under the stratified random sampling was used in drawing 756 examinees from a total of 1334 applicants who took the examination. The independent variables were gender, type of school, mathematical and verbal ability test The Fisher's Linear Discriminant Functions for two groups were:
h0= a0+a1X1+a2X2+...akXk (not admitted group)
h1= b0+b1X1+b2X2+...bkXk (admitted group).
The derived Fisher's linear discriminant functions for the two groups were: h0 = -3.976 + 9.489 E -2 x score (not admitted) hi = -7.917 + 0.141 x score (admitted) The resulting logistic regression model was: Logit (V) = -1.297 + 0.053 x score The logistic regression model showed that the score in mathematical and verbal ability test affected the examinees in the examination status. The discriminant model was the better model representing the factors of the examination since it gave a higher classification rate than the discriminant function.

Submitted to the University Library 04-17-2007 SP-3491