Introductory description

This module aims to provide those with no prior training in quantitative analysis, and who may not wish to conduct quantitative research with the tools to usefully interpret, evaluate, and use, quantitative research in their own work. It also serves as a foundation for ongoing study for those with no background at all in quantitative analysis.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Science and Quantitative Methods?
2. Using numbers to summarize and communicate
3. Principles of Measurement
4. Statistical Foundations and Hypotheses
5. Understanding Association and Causation
6. Regression
7. Group comparisons
8. Algorithms, Analytics, and ‘Big Data’
9. Effect sizes and intervals
10. Making Claims, Good Scientific Practice and Open Science

Learning outcomes

By the end of the module, students should be able to:

• Understand the core principles and uses of quantitative analysis in business research and science
• Understand the link between research questions, scientific hypotheses, and data analysis
• Be able to confidently read, interpret, and use the results of quantitative management research
• Have the skills to implement key types of quantitative analysis, and the foundations for further study

Indicative reading list

Reading lists can be found in Talis

Subject specific skills

An in-depth understanding of assumptions underlying quantitative analyses

An in-depth knowledge of the presented methods to answer management research questions.

Transferable skills

Problem solving abilities.
Communication skills.
Analytical skills.
Confidence as a user of management research.
Confidence as user of statistical software.