Quantitative and Big Data Methods module (BM41008)

Build on foundational skills in statistics and data handling to prepare you to work with complex biomedical datasets. 

​You will explore how data are collected, analysed, interpreted, and communicated in biomedical science. The module covers key concepts in exploratory data analysis, descriptive and inferential statistics, experimental design, epidemiology, and predictive modelling. You will also be introduced to the principles of big data and precision medicine, examining how large and complex datasets are used to improve our understanding of health and disease. 

​You'll develop critical reasoning skills by working with real-world data and learn to interpret and present results in a way that meets publication standards. 

​What you will learn 

​In this module, you will: 

• ​Develop quantitative skills to interpret, analyse, and present complex biomedical data 
• ​Apply statistical methods, including hypothesis testing and predictive modelling 
• ​Understand the principles of big data structures and handling in a biomedical context 
• ​Study epidemiology concepts and their application to research 
• ​Work with real-world datasets to develop critical scientific reasoning 

​By the end of this module, you will be able to: 

• ​Show knowledge of big data structures and core principles, including different data types and data handling 
• ​Interpret statistical analyses, including epidemiology concepts, and draw appropriate conclusions given study limitations 
• ​Apply skills in problem solving and data interpretation to real-world scientific and clinical datasets 
• ​Handle and present statistical and genomic data to publication standards​

Assignments / assessments

​​Coursework (100%) 

• ​Analysis of complex datasets with results presented as publication-quality figures and figure legends 

​This module does not have a final exam.​

Teaching methods / timetable

• ​​Interactive lectures 
• ​Online materials via My Dundee​