Statistics and Probability module (MA12003)

From predicting the weather to analysing financial markets and scientific data, statistics and probability help us understand patterns and make decisions in an uncertain world. In this module, you will learn how to turn data into insight, using mathematics to describe trends, model uncertainty, and support real-world decision making.

You will begin by exploring how data can be summarised, visualised, and interpreted, and how relationships between variables can be identified. You will then build a foundation in probability, learning how to calculate the likelihood of events and understand how randomness influences outcomes.

A central idea you will develop is sampling: how a subset of data can be used to understand a much larger population. You will learn how to make predictions from data and assess how reliable those predictions are.

You will study key probability distributions, including the binomial, Poisson, and normal distributions, and learn how they are used to model real processes. You will also explore correlation and regression, allowing you to analyse and predict relationships between variables, as well as trends and patterns in time series data.

Alongside the theory, you will use tools such as Microsoft Excel to analyse data, perform calculations, and present results clearly. These skills are essential across science, engineering, finance, and business, and provide a strong foundation for further study in mathematics, physics, and data-driven subjects.

What you will learn

In this module, you will:

• describe and interpret data using graphs and summary statistics
• calculate probabilities and understand random processes
• use sampling to draw conclusions about larger populations
• assess the reliability and uncertainty of predictions
• work with key probability distributions, including binomial and normal
• analyse relationships between variables using correlation and regression
• explore trends and patterns in time series data
• use Excel to perform calculations and present data effectively

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

• analyse and interpret data in a clear and meaningful way
• make predictions from data and evaluate their reliability
• calculate and apply probabilities in a range of contexts
• model real-world situations using probability distributions
• identify and describe relationships between variables
• use software tools to analyse and present data
• communicate statistical results clearly

Assignments / assessment

• coursework (20%)
  • lab report using Microsoft Excel
• final written exam (80%)

Teaching methods / timetable

There will be five hours of in-person teaching every week, including: 

• two lectures weekly
  • lectures cover key points of the week's content
  • in-class time is prioritised for interactive discussion
  • lecture notes covering the full module will be available before classes
  • video content for key concepts and selected topics will be available
• three hours of tutorials weekly
  • solve problems individually and in groups
  • learning support will be provided by your lecturer and other tutors