Run by Bangor Business School
15 Credits or 7.5 ECTS Credits
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.
Describing and summarising data; Probability and probability distributions; Principles of statistical inference; Correlation and regression analysis; Regression models for panel data.
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.
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.
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.
Demonstrate an understanding of basic statistical concepts, basic ideas of sampling and statistical inference.
Demonstrate a good foundation in research methods and techniques that can be applied in writing reports.
Obtain data from primary and secondary sources, and carry out investigations using summary statistics, graphs, techniques of exploratory data analysis, correlation and regression.
Formulate feasible research questions and strategies; and assemble, select and present the results of data analysis and data modelling.
Demonstrate computer skills for data analysis and modelling, and use statistical computer packages.
|2-hour written examination at the end of Semester 1||60|
Teaching and Learning Strategy
A weekly 2-hour lecture.
One 1-hour practical session per week.
Pre- and Co-requisite Modules
Courses including this module
Compulsory in courses:
- N3CH: MA Banking & Finance (Chartered Banker) year 1 (MA/BFCB)
- N3AB: MA Banking & Finance year 1 (MA/BIF)
- N3BB: MA Banking and Law year 1 (MA/LBANK)
- N2AQ: MA Management and Finance year 1 (MA/MANFIN)
- N4AK: MSc Accounting and Banking year 1 (MSC/ACB)
- N4AJ: MSc Accounting year 1 (MSC/ACC)
- N4AG: MSc Accounting and Finance year 1 (MSC/ACCFIN)
- N3AX: MSc Banking and Finance year 1 (MSC/BANKFIN)
- N3CK: MSc Banking & Finance (Chartered Banker) year 1 (MSC/BFCB)
- N3CM: MSc Finance (10 month) year 1 (MSC/FIN10)
- N3AJ: MSc Finance year 1 (MSC/FINANCE)
- N3BF: MSc Islamic Banking and Finance year 1 (MSC/IBF)
- N3CC: MSc Investment Management year 1 (MSC/IMGT)
- N3CR: MSc Investment Management (10 month) year 1 (MSC/IMGT10)
- N2AO: MSc Management and Finance year 1 (MSC/MANFIN)