Statistics
Build statistical intuition from first principles and progress to modern modelling, causal inference, survival analysis, epidemiology and research applications.
Learn Statistics at the right depth.
Start at the level that matches your current experience. You can move between routes as your knowledge and goals develop.
High School
Build confidence earlyClear explanations, exam-ready practice and curriculum-aware learning for GCSE, A-Level, AP, IB and equivalent programmes.
Undergraduate
Master university modulesStructured learning for lectures, problem sheets, assignments, examinations and deeper conceptual understanding at university level.
Postgraduate
Go beyond the textbookAdvanced methods, specialist topics, research workflows and technical support for MSc, MRes, doctoral and professional study.
Learn for Yourself
Skills without the pressureCareer development, curiosity, refreshers and practical projects—learn useful quantitative and computational skills at your own pace.
Start learning Statistics.
Focused courses combine clear explanation, structured progression and applied practice. Begin with one course or follow a broader pathway.
Statistics Foundations
A clear and intuitive introduction to data, probability, distributions, sampling, confidence intervals and statistical reasoning.
Regression & Statistical Modelling
Move from simple linear regression to multivariable models, interactions, diagnostics and practical interpretation.
Survival Analysis
Learn time-to-event analysis from Kaplan–Meier curves to Cox regression and modern survival modelling.
Probability & Data
Develop confidence with probability rules, conditional probability, random variables and data interpretation.
AP Statistics
A structured AP Statistics pathway covering exploratory analysis, probability, sampling, inference and regression.
A-Level Statistics
A focused route through the statistical ideas commonly encountered within A-Level Mathematics.
Statistics is more than one course.
Build breadth across the discipline or focus deeply on the topics most relevant to your studies, career or research.
Capability, not just course completion.
Learning Statistics should change what you can understand, analyse and create—not simply add another course to a list.
Build this capability progressively through explanation, examples, practice and application.
Build this capability progressively through explanation, examples, practice and application.
Build this capability progressively through explanation, examples, practice and application.
Build this capability progressively through explanation, examples, practice and application.
Build this capability progressively through explanation, examples, practice and application.
Build this capability progressively through explanation, examples, practice and application.
Understand it. Practise it. Apply it.
Courses are designed around progression rather than passive content consumption.
Understand
Build intuition firstConcepts are introduced clearly so you understand the reasoning before memorising procedures.
Explore
Make ideas visibleInteractive examples and visual explanations help connect abstract ideas to intuition.
Practise
Turn understanding into skillWork through structured examples, exercises and problems that increase gradually in difficulty.
Apply
Use what you learnedConnect your knowledge to examinations, university work, research, coding and real projects.
Stuck on a difficult statistics problem?
Learn independently when you can, then work with an expert when you need deeper explanation, feedback, exam preparation or help applying your knowledge.
Learning rarely stays inside one discipline.
Move across connected subjects as your interests, studies and career goals develop.
Mathematics
From algebra and calculus to proof, linear algebra and optimisation.
Data Science
Python, R, SQL, visualisation, machine learning and real projects.
Bioinformatics
Genomics, transcriptomics, single-cell, spatial and computational biology.
Computer Science
Programming, algorithms, software, databases, systems and artificial intelligence.