Module ASB-4101:
Research Methods

Module Facts

Run by Bangor Business School

15 Credits or 7.5 ECTS Credits

Semester 2

Organiser: Prof Kostas Nikolopoulos

Overall aims and purpose

To provide the student with knowledge of intermediate and advanced qualitative and quantitative research methods, and provide a basis in research methodology.

Course content

The content involves initially describing and summarising data and then a brief revision of probability and probability distributions. then we focus on principles of statistical inference followed by correlation and regression analysis including logit and probit models. Finally, we conclude with an introduction to regression models for panel data.

Assessment Criteria

threshold

Threshold: D- to D+ No major omissions or inaccuracies in the deployment of information/skills; Some grasp of theoretical/conceptual/practical elements; Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives.

good

Good: B- to B+ Much of the relevant information and skills mostly accurately deployed; Adequate grasp of theoretical/conceptual/practical elements; Fair integration of theory/practice/information in the pursuit of the assessed work's objectives; Some evidence of the use of creative and reflective skills.

High Standard: Very good performance; Most of the relevant information accurately deployed; Good grasp of theoretical/conceptual/practical elements; Good integration of theory/practice/information in pursuit of the assessed work's objectives; Evidence of the use of creative and reflective skills.

excellent

Excellent: A- to A* An outstanding performance, exceptionally able; The relevant information accurately deployed; Excellent grasp of theoretical/conceptual/practice elements; Good integration of theory/practice/information in pursuit of the assessed work's objectives; Strong evidence of the use of creative and reflective skills.

C- to C+

Another level: C- to C+ Good pass • Understands some topics; • Evidence of study; • Focussed answer with average structure; • Arguments presented vaguely; • Presence of some factual/computational errors;

Learning outcomes

  1. Demonstrate an understanding of basic statistical concepts, basic ideas of sampling and statistical inference.

  2. Demonstrate a good foundation in research methods and techniques that can be applied in writing reports.

  3. Obtain data from primary and secondary sources, and carry out investigations using summary statistics, graphs, techniques of exploratory data analysis, correlation and regression.

  4. Formulate feasible research questions and strategies; and assemble, select and present the results of data analysis and data modelling.

  5. Demonstrate computer skills for data analysis and modelling, and use statistical computer packages.

Assessment Methods

Type Name Description Weight
COURSEWORK Coursework

Typically analysis of past data (big data) and forecasting for a major financial index or currency in a horizon of 3-6 months

40
EXAM Final Exam Marl

Typically four equally weighted numerical questions and one theoretical one - from a pool of these five questions four need to be answered. A pocket calculator is essential and a formula sheet is given. Regression analysis and descriptive statistics , and sampling theory are always examined.

60

Teaching and Learning Strategy

Hours
Lecture

Six weekly 3-hour lectures: 18 lecturing hours in total- but done over three weeks. So every week there should be scheduled two 3h continuous lectures. Three weeks are dedicated to lecturing. These should be in a room where teamwork can be enabled and students should be always bringing their laptops, tablets and pocket calculators as very often numerical exercises and data retrieval take place in the class. Essential for two traditional whiteboards to exist as numerical exercises are solved in class.

18
Practical classes and workshops

Four weekly 3-hour tutorials-workshops: 12 tutorial hours in total- but done over two weeks. So every week there should be scheduled two 3h continuous lectures. Two weeks are dedicated to tutorials. These should be in a room where teamwork can be enabled and students should be always bringing their laptops, tablets and pocket calculators as very often numerical exercises and data retrieval take place in the class. Essential for two traditional whiteboards to exist as numerical exercises are solved in class. Good internet connection is needed in the room.

12
Private study

for every one hour of lecture or tutorial, there should be 4 hours of private study to digest the material covered and to complement with self-study of the book and solve similar exercises at home. At this time the 40% assignment also should be completed.

120

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Safety-Consciousness - Having an awareness of your immediate environment, and confidence in adhering to health and safety regulations
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • skills in recording and summarising transactions and other economic events; preparation of financial statements; analysis of the operations of business (for example, decision analysis, performance measurement and management control); financial analysis and projections (for example, analysis of financial ratios, discounted cash flow analysis, budgeting, financial risks)
  • Analysis, deduction and induction. Economic reasoning is highly deductive, and logical analysis is applied to assumption-based models. However, inductive reasoning is also important. The development of such analytical skills enhances students' problem-solving and decision-making ability.
  • Quantification and design. Data, and their effective organisation, presentation and analysis, are important in economics. The typical student will have some familiarity with the principal sources of economic information and data relevant to industry, commerce, society and government, and have had practice in organising it and presenting it informatively. This skill is important at all stages in the decision-making process.
  • An appreciation of the nature of the contexts in which finance can be seen as operating, including knowledge of the institutional framework necessary for understanding the role, operation and function of markets and financial institutions (e.g. the economic, legal, regulatory and tax environment, both national and international; the firm; the capital markets and the public sector).
  • An ability to interpret financial data including that arising in the context of the firm or household from accounting statements and data generated in financial markets. The interpretation may involve analysis using statistical and financial functions and procedures such as are routinely available in spreadsheets (eg Microsoft Excel) and statistical packages. It may assume the skills necessary to manipulate financial data and carry out statistical and econometric tests (e.g. estimation and interpretation of asset pricing models; financial modelling and projections; event studies and residuals analysis; elements of time series analysis, such as serial correlation mean reversion, and stochastic volatility).
  • An understanding of the factors influencing the investment behaviour and opportunities of private individuals (bonds, equities, and derivatives; risk aversion; risk/return trade-offs; portfolio management and performance measurement; pensions and long term savings; the tax treatment of savings and investments; international diversification; forex risk; objectives of and constraints on institutional investors and advisors).
  • People management: to include communications, team building, leadership and motivating others.
  • Problem solving and critical analysis: analysing facts and circumstances to determine the cause of a problem and identifying and selecting appropriate solutions.
  • Research: the ability to analyse and evaluate a range of business data, sources of information and appropriate methodologies, which includes the need for strong digital literacy, and to use that research for evidence-based decision-making.
  • Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.
  • Networking: an awareness of the interpersonal skills of effective listening, negotiating, persuasion and presentation and their use in generating business contacts.
  • Ability to work collaboratively both internally and with external customers and an awareness of mutual interdependence.
  • Ability to work with people from a range of cultures.
  • Articulating and effectively explaining information.
  • Building and maintaining relationships.
  • Communication and listening including the ability to produce clear, structured business communications in a variety of media.
  • Conceptual and critical thinking, analysis, synthesis and evaluation.
  • Self-management: a readiness to accept responsibility and flexibility, to be resilient, self-starting and appropriately assertive, to plan, organise and manage time.
  • Self reflection: self-analysis and an awareness/sensitivity to diversity in terms of people and cultures. This includes a continuing appetite for development.

Pre- and Co-requisite Modules

Pre-requisite of:

Courses including this module

Compulsory in courses: