Demonstrate a comprehensive understanding of data analysis in public health decision-making and the different types of data used in public health.

Knowledge & Understanding

Analysis

Enquiry


Effectively visualize data and interpret findings from epidemiological studies, understanding associations and causation in public health research.

Application

Knowledge & Understanding


Design and communicate data findings through reports and presentations, ensuring effective communication to diverse audiences, while adhering to principles of data governance and confidentiality.

Communication

Application

Utilising a provided data set, undertake data analysis and prepare a briefing paper highlighting the key findings and trends identified within the data. Data should be presented through a variety of visualisations, drawing attention to pertinent points and relevance to the particular public health issue under discussion.



This assessment will cover all learning outcomes.

Importance of data analysis in public health decision-making

Types of data used in public health (e.g., epidemiological, survey, administrative)

Data cleaning, validation, and transformation

Principles of data governance and confidentiality

Descriptive statistics

Measures of central tendency and dispersion (mean, median, mode, range)

Visualizing data (graphs, charts, tables)

Interpreting findings from epidemiological studies

Understanding associations and causation in public health research

Effective communication of data findings to diverse audiences

Designing reports and presentations for stakeholders

This module explores the critical role of data analysis in public health decision-making. Learn about various types of data used, including epidemiological and survey data, and essential techniques such as data cleaning, validation, and transformation. Understand principles of data governance, confidentiality, and descriptive statistics. Gain skills in visualizing data effectively through graphs, charts, and tables, and interpreting findings from epidemiological studies. Focus on understanding associations and causation in public health research and effectively communicating data findings to diverse stakeholders through well-designed reports and presentations.

Key concepts will be delivered through lead lectures delivered through the university’s Virtual Learning Environment. This will then be followed by online synchronous discussion groups/seminars allowing learners to explore key issues and discuss the application to their particular working contexts.

Magnuson, J.A. and Dixon, B.E. (2020) Public health informatics and information systems. Springer Nature.

Virtual Learning Environment (VLE)

Online learning resources and guides

Library and academic resources

Recorded supplementary material