Undergraduate Course: Data Analysis for Business 1 (BUST08060)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course introduces students to business research through a strong focus on statistics and data, and their role in informing effective business decisions. It forms the first course of a two-course quantitative research methods stream. The course demonstrates how data collection and statistical analysis underpin sound managerial and strategic choices. It begins by introducing students to key concepts in business research, including business ethics and literature reviews. This equips students not only to develop their own quantitative research projects, but also to critically evaluate and interpret academic and industry evidence, a core analytical skill throughout their undergraduate degree and particularly valuable for students intending to undertake quantitative dissertation research.
The course then develops a foundation in probability and statistics, with particular emphasis on how methodological choices shape the quality and interpretation of data. It highlights the importance of ethical data collection and responsible analysis. Students will learn practical techniques for collecting, coding, analysing, and synthesising data from a variety of sources. The course provides hands-on experience in generating and analysing quantitative datasets, enabling students to develop practical data analysis skills applicable to real business problems and to quantitative research projects. Data analysis techniques for this course will be supported with MS Excel.
Students wishing to pursue a mixed-methods research methods sequence of courses, which covers qualitative techniques in more depth alongside quantitative methods, should take Business Research Methods 1: Qualitative Inquiry and Business Research Methods 2: Quantitative Approaches. |
| Course description |
This course introduces students to the research process in business studies and practice, with a primary focus on the statistical analysis of business data. It forms the first component of a two-course quantitative research methods stream. The course begins with the fundamentals of business research and the philosophical underpinnings of research design. Students learn how to effectively read, review, and evaluate literature, develop research ideas, and formulate research questions. They will also reflect on ethical research practices and research rigour, considering what these mean for the quality of evidence underpinning business decision-making and for conducting their own research projects.
The course then moves from research design to the practical analysis of data and statistics. It examines how methodological choices shape the type and quality of data collected, and emphasises the ethical responsibilities involved in handling and interpreting data. The focus is on quantitative data analysis in business contexts, outlining systematic approaches to collecting, organising, coding, and interpreting data. Students will analyse data relating to people, organisations, and markets, learning how quantitative evidence can be used to understand behaviour and decision-making. They will work with a range of data sources and develop practical skills in synthesising evidence to generate meaningful business insights. The course provides hands-on experience in collecting and analysing quantitative data, enabling students to apply analytical techniques to real-world business questions and to quantitative research projects.
The course is structured around two blocks:
Block I: Foundations of Business Research
-Business Research and the Research Process
-Literature Review and Research Questions
-Research Approaches and Philosophies
-Research Ethics
Block II: Introduction to Probability and Statistics
-Data and Statistics
-Probability
-Probability Distributions
-Sampling
-Statistical Inference
Student learning experience:
The course aims to support students in developing the skills and capabilities to undertake independent research and become critical thinkers, starting from reviewing scholarly literature, problematising the field and identifying gaps, designing appropriate research strategies, and selecting appropriate research methods to address these gaps, all the way to analysing and interpreting data and presenting research findings. By learning how to do research and justify and present their methodological choices with confidence and rigour, students will also learn how to evaluate research evidence to support decision-making in business contexts. The course will thus better equip them for the world of business as well as their final year when undertaking their own independent dissertation research.
The course is designed to be hands-on providing students with the opportunity to learn by conducting research and analysing data, in addition to understanding the theoretical underpinnings of business research decisions that shape society.
Interactive lectures present critical overviews of key concepts, processes, and debates within the subject, relating these to a wide range of current examples of research in business practice. Tutorials are designed to give students the opportunity to work in groups and apply their learning, providing a practical experience with the research process and specific methods. It is expected that students engage with readings and activities in advance of each class and actively contribute to, and participate in, classroom debates. The aim is to foster a collaborative, non-judgemental, and inclusive learning environment.
|
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2026/27, Available to all students (SV1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 8,
Fieldwork Hours 4,
Online Activities 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
154 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
60% Project Report (Individual), 2,000 words - Assesses course Learning Outcomes 1,4,5
40% Literature Review (Individual), 1,800 words - Assesses course Learning Outcomes 1,2,3 |
| Feedback |
Formative feedback: will be given in class during the discussion sessions, in project advice meetings, as well as on all submitted coursework.
Summative Feedback: Feedback on coursework, together with individual marks, will be provided on Learn within agreed deadlines. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Explain the nature and scope of business research, including the research process and key philosophical foundations.
- Critically review and evaluate academic and professional literature relevant to business and management topics, and produce a structured literature review.
- Define research problems and formulate research questions grounded in real-world business phenomena and existing literature.
- Describe and evaluate quantitative research approaches and methods, including their appropriate application, limitations, and ethical considerations.
- Apply basic quantitative methods in business research, including data collection, organisation, statistical analysis, and the communication of findings.
|
Reading List
Bell, E., Bryman, A. & Harley, B. (2022).¿Business research methods. Oxford University Press.
Anderson, D. et al. (2024). Statistics for Business and Economics, Cengage. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Business research,literature review,research methods,quantitative research,statistics,data analysis |
Contacts
| Course organiser | Dr Nicholas Myers
Tel:
Email: Nick.Myers@ed.ac.uk |
Course secretary | |
|
|
University Homepage