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Study information

Advanced Research Methods and Analysis

Module titleAdvanced Research Methods and Analysis
Module codeBEMM216
Academic year2024/5
Module staff

Dr Justin Tumlinson (Convenor)

Duration: Term123
Duration: Weeks


Number students taking module (anticipated)


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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching activities 18Workshops: 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 9Seminars will allow supervised application of concepts
Guided independent study54Read and prepare all assigned chapters and articles prior to each session
Guided independent study20Computer-based assessment: Executing and writing up computational assessment
Guided independent study46Exam preparation: Revising for the exam
Guided independent study3Exam: Writing the scheduled exam

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Review of individual performance on exercisesRegular feedback in lecture1-6Verbal feedback to individual students and groups

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Assignment: computer-based statistical analysis30Issued during Seminar 6. Due during Lecture 91-6Written feedback
Assignment: Exam70During exam week (180 minutes)1-6Written feedback

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Assignment: computer-based statistical analysisAssignment: computer-based statistical analysis1-6Referral/deferral period
Assignment: statistical analysis and using qualitative softwareAssignment: statistical analysis and using qualitative software1-6Referral/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.)

Key words search

Advanced Research Methods Analysis, Quantitative Methods, Regression, Statistical Analysis

Credit value15
Module ECTS


Module pre-requisites


Module co-requisites


NQF level (module)


Available as distance learning?


Origin date


Last revision date