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In this module you will build on your understanding from the Applied Epidemiology and Statistics for Public Health modules of the MPH.
You will develop further your knowledge and skills of quantitative research methods relevant to public health data analysis and public health intelligence. You will use Stata statistical software to build on skills developed earlier in the programme and be introduced to R, and signposted to other relevant software packages.
You will learn about alternative study designs (e.g. quasi-experimental), the wide range of data sources relevant for public health, and about emerging technologies such as AI, machine learning, digital transformation and big data and their potential influence in public health. You will learn how these approaches are important as computing resources and large administrative health datasets become more available, presenting both challenges and opportunities for public health research. You will take a critical view of the whole research pathway from data sourcing to dissemination, for example, how the decisions made can contribute to or reduce health inequalities.
Aims of the module
The aim of this module is to provide students with a deeper understanding of quantitative methods and their relevance to public health. The module will build on methods covered in the Applied Epidemiology and Statistics for Public Health modules and introduce students to alternative study designs, a wider selection of statistical techniques, evidence synthesis and approaches for interpretation, presentation, and communication of complex health data to technical and non-technical audiences.