Module overview
Modern engineering is driven by data. From monitoring the performance of complex systems and validating experimental results to developing predictive models and improving product reliability, engineers increasingly rely on statistical methods to make informed decisions. This module develops the statistical knowledge and analytical skills needed to extract meaningful insights from engineering data.
You will learn how engineers use exploratory data analysis, hypothesis testing and regression techniques to investigate engineering problems and quantify uncertainty. Working with real-world engineering datasets, you will develop practical experience of statistical software while learning how to build, interpret and evaluate statistical models. Throughout the module, emphasis is placed on selecting appropriate analytical methods, understanding the assumptions behind statistical models and communicating data-driven conclusions effectively.
By the end of the module, you will be able to apply statistical modelling techniques confidently to engineering problems, supporting evidence-based decision-making in areas such as product development, experimental research, quality engineering, manufacturing and systems optimisation.