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Advanced Research Methods in Marketing - MAN00141M

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  • Department: The York Management School
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2024-25
    • See module specification for other years: 2023-24

Module will run

Occurrence Teaching period
A Semester 2 2024-25

Module aims

This module aims to empower students to do marketing research, ready for incorporation into their dissertations, presentations, and research papers. It will build on what they have learnt in the Research in Marketing module in Semester 1.

The module will enable students to appreciate how marketing problems are turned into appropriate research questions, the philosophical paradigms in marketing research, how the nature of the research questions guides the methods of data collection, and how that in turn dictates the analytical approaches. The module will also provide students with hands-on experience of analysing data.

Module learning outcomes

By the end of this module, you will be able to:

• Articulate appropriate research questions to address marketing issues while demonstrating a basic understanding of the philosophy of research

• Appreciate the differences between correlational and causal research and choose appropriate data collection methods to address research questions while bearing ethical considerations in mind

• Understand different quantitative data types (e.g., categorical, numerical) and the most appropriate analytical approach for each

• Code and analyse qualitative data (e.g., grounded theory, quantitative content analysis)

• Gain exposure in carrying out data analysis using tools such as SPSS

• Interpret data to write the results section of a dissertation/research project.

Skills-related learning outcomes

• Think critically to produce logical and structured arguments supported by relevant evidence.

• Sharpen your academic writing and referencing skills.

Module content

• Philosophical paradigms in marketing research

• Correlation vs. causation and experimental design

• Different approaches of data collection

• Conducting qualitative and quantitative data analysis (e.g., content analysis, t-tests, ANOVA, correlation, regression)

• Academic writing including but not limited to reporting of the findings

Indicative assessment

Task % of module mark
Essay/coursework 70
Essay/coursework 30

Special assessment rules

None

Indicative reassessment

Task % of module mark
Closed/in-person Exam (Centrally scheduled) 30
Essay/coursework 70

Module feedback

Students submitting formative assessments will receive written feedback.

For the summative assessment, students will receive a detailed feedback sheet. Turnaround time will be consistent with the departmental policy. At the end of term a module self-evaluation report will be prepared to be approved by the Board of Examiners and uploaded onto the VLE.

Indicative reading

Bryman & Bell (2015) Business Research Methods (4th ed.). Oxford: OUP.

Gravetter, F. J., & Forzano, L. B. (2015). Research Methods for the Behavioral Sciences (5th ed.). Belmont, CA: Wadsworth Publishing.

Pallant, J. (2005). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (version 12). Open University Press.



The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.