Likelihood of passing the certified public accountant board examination of CvSU students : a multivariate approach / by Eusebio L. Bawar II and Joan Ericka D. Ubalde.

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Indang, Cavite : 2017. Cavite State University- Main Campus,Description: xiv, 64 pages : illustrations ; 28 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
Subject(s): DDC classification:
  • 657.092  B32 2017
Online resources: Production credits:
  • College of Arts and Science (CAS)
Abstract: BAWAR, EUSEBIO L. Il & UBALDE , JOAN ERICKA D. Likelihood of Passing the Certified Public Accountant Board Examination of CvSU Students: A Multivariate Approach. Undergraduate Thesis. Bachelor of Science in Applied Mathematics with specialisation in Statistics. Cavite State University, Indang, Cavite. May 2017. Adviser: Prof. Analyn A. Mojica. This study was conducted to determine the likelihood of passing the certified public accountant (CPA) board examination among accountancy students of Cavite State University. It also intended to assess which predictor(s) included significantly predicts success in the performance of the said exam. Secondary data was gathered and used prior to this study. Among the predictor variables, only two were found to be significant to the CPA board exam. Via three methods of checking and selecting the best model, Financial Accounting and Reporting 1 was found to be a good predictor of success in the performance of accountancy students. Three logit models were formulated under Financial Accounting and Reporting 1 namely for “conditional”, “failed” and “passed” which are as follows: logit [Vcondi] = -9.604 + 0.135x3 logit [Vraitea] = -9.266 + 0.122x; logit [¥conai] = -13.533 + 0.21 1x3 These models were needed to find the value per status or likelihood of passing the board exam. High scores on Financial Accounting and Reporting 1 during the qualifying exam resolved passing rate while lower ones deemed either conditional or failing rate. Though Financial Accounting and Reporting 1 already predicted likelihood of success, more predictor variables added greater predictive power as well as increase in sample size.
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Theses / Manuscripts Theses / Manuscripts Ladislao N. Diwa Memorial Library Theses Section Non-fiction 657.092 B32 2017 (Browse shelf(Opens below)) Link to resource Room use only T-6786 00011341

Thesis (BS Applied Mathematics) Cavite State University

Includes bibliographical references.

College of Arts and Science (CAS)

BAWAR, EUSEBIO L. Il & UBALDE , JOAN ERICKA D. Likelihood of Passing the Certified Public Accountant Board Examination of CvSU Students: A Multivariate Approach. Undergraduate Thesis. Bachelor of Science in Applied Mathematics with specialisation in Statistics. Cavite State University, Indang, Cavite. May 2017. Adviser: Prof. Analyn A. Mojica.

This study was conducted to determine the likelihood of passing the certified public accountant (CPA) board examination among accountancy students of Cavite State University. It also intended to assess which predictor(s) included significantly predicts success in the performance of the said exam.

Secondary data was gathered and used prior to this study. Among the predictor variables, only two were found to be significant to the CPA board exam. Via three methods of checking and selecting the best model, Financial Accounting and Reporting 1 was found to be a good predictor of success in the performance of accountancy students.

Three logit models were formulated under Financial Accounting and Reporting 1 namely for “conditional”, “failed” and “passed” which are as follows:

logit [Vcondi] = -9.604 + 0.135x3
logit [Vraitea] = -9.266 + 0.122x;
logit [¥conai] = -13.533 + 0.21 1x3

These models were needed to find the value per status or likelihood of passing the board exam. High scores on Financial Accounting and Reporting 1 during the qualifying exam resolved passing rate while lower ones deemed either conditional or failing rate.

Though Financial Accounting and Reporting 1 already predicted likelihood of success, more predictor variables added greater predictive power as well as increase in sample size.

Submitted copy to the University Library. 08-01-2017 T-6786

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