Advanced Research Methods and Analysis
| Module title | Advanced Research Methods and Analysis |
|---|---|
| Module code | BEMM216 |
| Academic year | 2024/5 |
| Credits | 15 |
| Module staff | Dr Justin Tumlinson (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 10 |
|---|
Module description
This module prepares students to undertake quantitative research in the field of management, as well as critically understand and evaluate such work by others, especially as published in academic journals. The primary method discussed is regression, beginning with a review of underpinning probability and statistics. It takes an applied approach, focusing on the consequences and use of the fundamental assumptions rather than their theoretical derivations.
Module aims - intentions of the module
This module aims to instill the fundamentals of applied regression analysis, expose students to software tools to execute it, and enable critical analysis of regression-based research.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Formulate quantitative research questions suitable to statistical analysis;
- 2. Critically discuss and evaluate quantitative research methods avaliable for management research.
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Be able to identify threats to validity in existing quantitative research;
- 4. Apply robustness improving techniques to ensure validity of quantitative research;
- 5. Apply probability and statistics to everyday situations.
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 6. Discuss the limitations of specific methodological approaches for own research.
Syllabus plan
Indicative topics may include the following:
- Research Questions and Data
- Review of Probability
- Review of Statistics
- Linear Regression with One Regressor
- Hypothesis Tests & Confidence Intervals w/ 1 Regressor
- Linear Regression with Multiple Regressors
- Hypothesis Tests & Confidence Intervals w/ Multiple Regressors
- Nonlinear Regression Functions
- Assessing Studies Based on Multiple Regression
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 27 | 123 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching activities | 18 | Workshops: The lecture will involve a tutor-led but not dominated discussion of key methods to develop an in-depth understanding of each research method |
| Scheduled Learning and Teaching activities | 9 | Seminars will allow supervised application of concepts |
| Guided independent study | 54 | Read and prepare all assigned chapters and articles prior to each session |
| Guided independent study | 20 | Computer-based assessment: Executing and writing up computational assessment |
| Guided independent study | 46 | Exam preparation: Revising for the exam |
| Guided independent study | 3 | Exam: Writing the scheduled exam |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Review of individual performance on exercises | Regular feedback in lecture | 1-6 | Verbal feedback to individual students and groups |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 0 | 0 | 100 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Assignment: computer-based statistical analysis | 30 | Issued during Seminar 6. Due during Lecture 9 | 1-6 | Written feedback |
| Assignment: Exam | 70 | During exam week (180 minutes) | 1-6 | Written feedback |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Assignment: computer-based statistical analysis | Assignment: computer-based statistical analysis | 1-6 | Referral/deferral period |
| Assignment: statistical analysis and using qualitative software | Assignment: statistical analysis and using qualitative software | 1-6 | Referral/deferral period |
Indicative learning resources - Basic reading
(1) Introduction to Econometrics, 4th Edition by Stock & Watson.
(2) Selected journal articles (e.g., Hegde & Tumlinson (2021). “Information frictions and entrepreneurship.” Strategic Management Journal.)
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 25/02/2019 |
| Last revision date | 10/05/2024 |
