This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

This comprehensive course bridges the gap between foundational statistical reasoning and practical applications related to business and engineering decision-making. Throughout the course, we’ll ...

Introduction to Big Data (DT102) provides the fundamentals needed to allow organizations to turn data into actionable information. Starting with an overview of big data, which covers key enterprise ...

The purpose of the course is to introduce the statistical methods that are critical in the performance analysis and selection of information systems and networks. It includes fundamental topics as ...

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 ...

This course introduces students to statistics and quantitative information. The course surveys probability theory, hypothesis testing, descriptive statistics and visualizations, and inferential ...

Course planning information Course notes Access to a Computer with Excel is required. Expected prior learning Students must have a good grounding in basic maths. It is strongly recommended that ...

An introduction to statistics in an agricultural and horticultural context, including the presentation, analysis and interpretation of quantitative data. The fourth number of the course code shows the ...

Statistics is a discipline that is closely allied to mathematics. The principal task of statistics is the collection and analysis of data using various techniques and then presenting the results in ...