In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

This campus-based module is led by Stephen Walters. It runs in the Autumn semester and is worth 15 credits. This module introduces students to the basic concepts and techniques of medical statistics, ...

Data Science combines scientific inquiry, statistical knowledge and computer programming with a focus on learning powerful insights from big data. Businesses use data to plan, evaluate, innovate, and ...

The field of data analytics is developing rapidly. With the rise of ever larger and more specialised datasets, it’s essential to understand how to collect, handle, evaluate and interpret data to ...

Sections 11.1, 11.2 and 11.3 Accuracy, impartiality, clarity and credibility are as important when numerical values and data are deployed in the BBC's output as they are in the rest of its journalism ...

Introduction to Data Visualisation and Web Applications Using R This course introduces the key aspects of data visualisation using R, with applications of powerful R tools to generate clear graphics ...

This guidance note discusses how to report statistics and data, while avoiding some of the pitfalls. Advice in assessing the creditability of data-based stories; statistical checking or how to report ...

Whatever study you choose to conduct, it will probably have a target population. The target population is the group of people who could be involved in your study. For example, if you wanted to do some ...