Statistical Science (Distance Learning) (Taught)

The Statistical Science MSc is a part-time distance learning programme, offering you the flexibility to study your way. You will develop the advanced techniques and skills required to be a successful statistician in the 21st century.

As the data we generate increases, so does the global demand for analysts who can apply modern statistical methods to make sense of it. The MSc ensures you will gain the skills to go from exploring a data set, to modelling and analysing the data, through to presenting your findings in a variety of ways.

You will develop:

• essential statistical knowledge

• analytical skills

• computational expertise

• interpretive and communicative skills

Teaching is provided through course materials including lecture notes, digital recordings, training videos and practical computer sessions. You have the flexibility to look at these in your own time, meaning you can complete the masters around other commitments. We will support you throughout the degree with live online sessions using Microsoft Teams (or similar) which gives you the opportunity to ask any questions you have about the module content.

You will study the core statistical concepts of inference and modelling. As you progress, you will cover advanced topics in machine learning, multivariate statistics and time series. These topics will develop your understanding of modern statistical techniques, leading to a dissertation which lets you demonstrate the skills you have gained and develop your ability to study independently. You will be supported by expert lecturers and leading statistical experts and researchers throughout the MSc.

Continued Professional Development (CPD)
If you are already working in a statistics-related role, this MSc will enhance your existing knowledge and skills. You will formalise and consolidate your learning and practical skills through carefully chosen modules.

All of the modules are available as standalone units to enhance your career development. Some examples include:

• Frequentist Statistical Inference - learn the fundamentals of statistical inference and the computational implementation of inferential methods

• Statistical Modelling of Discrete and Survival Data - explore extensions of linear models which enable the analysis of data in a wide range of scenarios

• Statistical Machine Learning - use modern methods, combining statistics and computation, to make predictions for real-life data sets