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.
thresholdNo 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.
goodMuch 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.
excellentAn 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)