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Quantitative Research Methods and Data Analytics (BUS229)

Semester: A
Level: 5
Module code: BUS229
Module organiser: Dr Panos Panagiotopoulos

Module Overview

The module will provide an overview of quantitative methods in business and management research. Following a revision of descriptive statistics and inference, the focus will be on fitting models, synthesising and communicating the results. The module will then discuss different types and sources of quantitative data before advancing on more contemporary issues of data applications and analytics (e. g. government data, clickstreams, web and social media analytics). Emphasis will be placed on the use of statistical software with practical examples and interpretation of results.


The proposed module will advance students' knowledge of quantitative methods and train them in completing research projects involving data analysis (e. g. surveys or online information sources). Upon completion, students will be able to identify a relevant research topic and conduct an independent project while being sensitive to issues of validity and reliability of the outcomes. They should also be able to collect, clean and analyse data from different sources using appropriate software; this experience will help students to communicate with statistical experts and data scientists in a modern workplace.

Indicative lecture topics:

• Types and sources of quantitative data
• Reviewing the literature and formulating questions/hypotheses
• Bivariate analysis and comparing means
• Simple and multiple regression with diagnostics
• Survey research
• Research ethics and integrity
• Introduction to big data and analytics
• Big data applications in business and society

Learning Outcome

By the end of the module, you should have acquired:

• Describe the key concepts related to the collection and analysis of quantitative data using appropriate statistical techniques
• Apply and effectively interpret the results of statistical analysis methods in business research
• Design and execute a provisional area of independent research that could be the basis for a final year undergraduate dissertation or extended essay
• Demonstrate understanding of the key concepts and implications of data analytics
• Demonstrate effective problem solving and decision making using appropriate quantitative and qualitative skills including identifying, formulating and solving business problems
• Develop numeracy and quantitative skills including data analysis, interpretation and extrapolation
• Demonstrate the ability to conduct research into business and management issues, either individually or as part of a team for projects dissertations/presentations

Graduate Attributes and Transferable Skills

• Use quantitative data confidently and competently (e. g. descriptive statistics, regression analysis)
• Use technologies to access, interpret and critically evaluate the usefulness of data from different information sources (e. g. open government data)
• Apply analytical and problem-solving skills to produce evidence-based and creative thinking
• Develop a strong sense of research ethics and intellectual integrity
• Communicate competently with data scientists and other professionals in the area of business statistics


• 30% Mid-Term Test
• 70% Essay

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