01
Algebra and functions
Build confidence with expressions, equations, inequalities, functions, graphs and symbolic manipulation.
Mathematics pathway
Build the mathematics behind quantitative learning.
This pathway supports learners who need stronger mathematical foundations for statistics, data science, modelling and applied quantitative subjects.
Suggested route
02
Calculus foundations
Understand limits, differentiation, integration, rates of change and areas under curves.
03
Linear algebra
Study vectors, matrices, systems of equations, transformations and the ideas behind multivariable methods.
04
Probability and uncertainty
Connect mathematical probability with statistical reasoning, random variables and uncertainty.
05
Applied problem-solving
Use mathematical reasoning to support statistics, data science, modelling and quantitative decision-making.
Recommended resources
Read these guides alongside the pathway.
Statistics · Foundation
How to choose the correct statistical test
6 min read · Updated 5 June 2026
A detailed guide for students deciding between t-tests, ANOVA, chi-square tests, correlation, regression, logistic regression and non-parametric methods.
Statistics · Foundation
Understanding p-values, confidence intervals and effect sizes
6 min read · Updated 5 June 2026
A detailed guide explaining statistical significance, uncertainty, effect size, practical importance and how students should interpret results responsibly.
Regression · Foundation
Choosing between correlation and regression
6 min read · Updated 5 June 2026
A detailed guide helping students understand when to use correlation, when to use regression, and why the research question matters more than the software menu.
Regression · Intermediate
Linear regression assumptions and diagnostics
5 min read · Updated 5 June 2026
A detailed guide to the assumptions behind linear regression, why they matter, how students should think about diagnostics and how to report limitations clearly.
Research methods · Advanced
Sample size, power and precision explained
6 min read · Updated 5 June 2026
An advanced guide explaining sample size, statistical power, precision, effect size, uncertainty and why planning should focus on estimation as well as hypothesis testing.
Statistics · Advanced
Multiple testing and false discovery rate
5 min read · Updated 5 June 2026
An advanced guide explaining why repeated hypothesis testing increases false positives, how family-wise error and false discovery rate differ, and how to report multiple-testing corrections.
Need guidance?
Submit enquiry → review → match.
If you are unsure which mathematical foundation to strengthen, submit an enquiry with your level and topic.
Submit enquiry