Module Description
Research Overview

This course focuses on the philosophy of research, comparison of qualitative and quantitative, and mixed method research, motivation of studies. The course also covers the identification of research problem and problem solving. 

Literature Review and Conceptual Framework

This course focuses on a Literature Review on a specific accounting topic. The purpose of this course is to get familiar with background/ history of problem; identify possible ways to study the problem; assess strengths and weaknesses of previous studies; and develop conceptual framework & rationale for present/future study.

Research Design & Research Ethics

The course covers the use of scientific research as a problem-solving tool. This encompasses the understanding and application of appropriate research designs. The course also includes discussions on ethical principles supporting research policies. 

Research Analysis

The course covers statistical analysis techniques and the use of computer for data analyses.Topics covers introduction to statistics, fundamentals of probability, random variable and probability distributions, sampling distributions, ANOVA, simple regression, chi square applications, non-parametric statistics and multi-variate data analysis and factor analysis.

Techniques of Writing Research Proposal

The course focuses on various research techniques of writing research proposal.  It is aimed at equipping the student in writing a detailed research plan (proposal) including problem identification and selection, research questions/ hypotheses, literature review, methodological design, sampling design, development of data gathering instruments, and data collection techniques

Proposal Preparation - Finalizing and presenting

Ready for Proposal Defence. Submission of Final Draft Proposal

Advanced Statistical Data Analysis

This course is intended to help students to learn how to analyze quantitative data.  The course focuses more on advanced forms of regression based analysis including multiple regressions, logistic regressions, general linear modeling and structural equation modeling.