Module Title: Research Methods
Module Director: Professor Kostas Nikolopoulos
Core Module: Full and Accelerated Programmes
The overall aim of this module is to equip students with research tools which can be used in their study of other modules and in their mini projects. The course also serves as a foundation for further study of more advanced research methods for those students who wish to pursue higher degrees. The module starts with an introduction to research methodology and information technology tools. The main part of the module comprises an introduction to techniques of describing and summarising data; elements of data modelling; principles of probability and inference; regression analysis, time series analysis and survey methodology.
Aims & Objectives
On completing this module students will:
Understand how and why research methods is a key component of the global economy
Provide a good foundation in research methods and techniques that students can use and build up on when writing any academic or non-academic report
Critically analyse data from primary and secondary sources
Formulate feasible research questions and assemble, select and present the results of data analysis and modelling
Be able to critically evaluate and interpret research data presented to them in their day to day roles.
Research Methods for Business: A Skill Building Approach—7th Edition Uma Sekaran & Roger Bougie
Means of Assessment:
This module is assessed by means of an individual assignment (40%) and examination (60%)
Introduction to Research, Data sources and Descriptive Statistics
The broad objective of this section is to provide an overview of the role of research in business and to provide a description of the data sources that are available to facilitate research. The unit concludes with an introduction to descriptive statistics and graphical methods.
Introduction to Inferential Statistics: Hypothesis Testing, Correlation and Regression Analysis
In this unit we focus our attention on more advanced (or inferential) statistical techniques. At the heart of this is the idea that we can use data and statistical analysis to inform decision making. The unit will begin by describing the basic process of hypothesis testing and some of the statistical theory that underpin these techniques. Then the unit will go on to describe and demonstrate several different scenarios and accompanying techniques that can be used to extract information from data. This unit relies on the us e statistical tables and a number of different statistical tests that can be conducted to test hypotheses or theories.
The second section in this unit will introduce students to correlation and regression analysis. In this section we will delve more deeply into the underlying relationships that may exist between variables. The broad idea is to examine how data can be used to increase our understanding of outcomes that may be of interest to our organizations.
In this study guide we introduce the concept of research design and highlight some of the main forms of research design, highlighting the relative strengths and weaknesses of each. The introductory section of this unit will introduce a number of key concepts in research design, before going more deeply into the various ways in which quantitative research studies can be conducted.
We will then turn to research design, commencing with what is, at least in theory, the best form of research design – experimentation – and describe why it is generally viewed as being the ‘gold standard’ for research. It is also the most difficult to conduct and in many cases not possible. If we are unable to inform research questions through experimental methods, then it is important to understand the compromises being made in the use of different methodologies. A key objective of this study guide is to establish the limits of what different research designs can tell us. A serious concern is that we over-estimate what we think we can learn from research. The key to making good use of research is knowing its limitations and shortcomings.
The study guide concludes with a discussion on sampling techniques. A recurring theme in this module is that doing good, rigorous research is difficult and can be expensive and time-consuming. A key objective is to identify the compromises that we must make when we trade rigour for expedience – sometimes a necessary trade-off. The options for sampling techniques follow a similar discussion.