Mathematics (BSc) - UBC | Undergraduate Programs and Admissions

Your Mathematics degree provides a firm foundation in pure mathematics that you can apply in areas where it is of vital importance such as finance, computer science, and cryptography. The curriculum emphasizes powerful and versatile modes of thought including abstraction, critical thinking and logical analysis. You will also study the art of problem solving using logic, precision, intuition, and imagination

This program is also offered at UBC's Vancouver Campus

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Program information

Campus: Okanagan
Faculty: Irving K. Barber School of Arts and Sciences
Degree: Bachelor of Science

Length 4 yrs
Co-op Yes
You can combine your studies with full-time, paid work at top local and international organizations.
Honours Yes
You can study intense specialization in a single field.

You can select a concentration in Applied Mathematics, Pure Mathematics, or Statistics. Graduates of the Mathematics program are prepared for direct entry into careers in actuarial science, government, or finance. Many graduates go on to graduate studies, professional secondary teaching programs, or other professional programs.

Undergraduate research

You have the option of completing directed studies, where you will undertake a supervised investigation of an assigned topic, culminating in a project and oral presentation. The Irving K. Barber School of Arts and Sciences holds an annual undergraduate research conference on UBC’s Okanagan campus to showcase student research projects.

MATH 100 - Differential Calculus with Applications to Physical Sciences and Engineering
Derivatives of elementary functions, limits. Covers applications and modelling: graphing and optimization.
MATH 101 - Integral Calculus with Applications to Physical Sciences and Engineering
Definite integral, integration techniques, applications, modelling, linear ODE's.
COSC 111 - Computer Programming I
Introduction to the design, implementation, and understanding of computer programs. Topics include problem solving, algorithm design, and data and procedural abstraction, with emphasis on the development of working programs. This course should be followed by COSC 121.
COSC 121 - Computer Programming II
Advanced programming in the application of software engineering techniques to the design and implementation of programs manipulating complex data structures.
CHEM 111 - Principles of Chemistry I
Stoichiometry, atomic and molecular structure, chemical periodicity, gases, liquids, solids, and solutions. Not open to students with Chemistry 12.

MATH 200 - Calculus III
Analytic geometry in two and three dimensions, partial and directional derivatives, chain rule, maxima and minima, second derivative test, Lagrange multipliers, multiple integrals with applications.
MATH 220 - Mathematical Proof
Sets and functions; induction; cardinality; properties of the real numbers; sequences, series, and limits. Logic, structure, style, and clarity of proofs emphasized throughout.
STAT 230 - Introductory Statistics
Applied statistics for students with a first-year calculus background. Estimation and testing of hypotheses, problem formulation, models and basic methods in analysis of variance, linear regression, and non-parametrics. Descriptive statistics and probability are presented as a basis for such procedures.
MATH 225 - Introduction to Differential Equations
First-order equations, initial value problems, existence and uniqueness theorems, second-order linear equations, superposition of solutions, independence, general solutions, non-homogeneous equations, phaseplane analysis, numerical methods, matrix methods for linear systems, and applications of differential equations to the physical, biological, and social sciences.
COSC 221 - Introduction to Discrete Structures
Introduction to sets, logic, combinatorics, and graph theory, as applied in computing: sets and propositions, permutations and combinations, graphs and trees, Boolean algebra, algorithms, and applications.

MATH 307 - Applied Linear Algebra
Dependence/independence, bases and orthogonality; linear transformations from Rⁿ to R^m; change of basis; triangularization; quadratic forms in variables.
MATH 311 - Abstract Algebra I
Properties of integers, the integers modulo n, groups, subgroups, cyclic groups, permutation groups, linear groups, quotient groups and homomorphisms, isomorphism theorems, direct products, and an introduction to rings and fields.
MATH 319 - Introduction to Partial Differential Equations
Methods of separation of variable, Fourier series, heat, wave and Laplace's equations, boundary value problems, eigenfunction expansions, and Sturm-Liouville problems.
MATH 327 - Analysis I
Provides a rigorous foundation of calculus. Real numbers; limits and continuous functions; differentiation; elementary functions; the elementary real integral; normed vector spaces.
STAT 303 - Introduction to Probability
Basic notions of probability, random variables, expectation and conditional expectation and limit theorems.

MATH 459 - Mathematical Biology
Mathematical modelling in biological disciplines such as population dynamics, ecology, pattern formation, tumour growth, immune response, biomechanics, and epidemiology. Theory of such models formulated as difference equations, ordinary differential equations, and partial differential equations.
MATH 442 - Optimization in Graphs and Networks
Basic graph theory, emphasizing trees, tree growing algorithms, and proof techniques. Problems chosen from: shortest paths, maximum flows, minimum cost flows, matchings, graph colouring. Linear programming duality will be an important tool.
DATA 407 - Sampling and Design
Planning and practice of data collection. Pros and cons of both observational and experimental data. Survey samples: random sampling; bias and variance; unequal probability sampling; systematic, multistage, and stratified sampling; ratio and regression estimators. Experimental design: simple one-way comparisons; designs with randomization restrictions including blocking, split-plots, nested and repeated measures designs.
STAT 401 - Probability and Statistical Inference
Formal introduction to the theory of statistical modeling with a focus on distributions of data, likelihood based inference for learning unknown parameters, construction of confidence intervals and development of tests. Bayesian methods will be used to contrast standard statistical procedures.
MATH 461 - Continuous Optimization
Convex analysis, non-smooth optimization, Karush-Kuhn-Tucker theorem, iterative methods.

Your future

A UBC education will introduce you to people and ideas from around the world, open doors to new opportunities, and take you places you never imagined. You’ll graduate not only with expertise in your chosen field, but with the skills you need to continue growing, learning, and evolving with your career over time.

English-language requirements

English is the language of instruction at UBC. All prospective students must demonstrate English-language competency prior to admission. There are numerous ways to meet the English Language Admission Standard.

General admission requirements

Completion of the IB Diploma with a minimum score of 24 points, including at least three Higher Level courses and additional points for Extended Essay and Theory of Knowledge.
Completion of Standard Level or Higher Level English A at a minimum score of 3, where English is the primary language of instruction.

Degree-specific requirements: Science

IB Mathematics (Standard or Higher Level; IB Math Studies does not meet the requirement)
One of IB Biology, IB Chemistry, IB Physics, or IB Geography (Standard or Higher Level)
Chemistry at the junior or Grade 11 level
Physics at the junior or Grade 11 level (strongly recommended)

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This program is also offered at UBC's Vancouver Campus

Undergraduate research

What you need to know

What can you do with this major after graduation?

Your future

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Program requirements

English-language requirements

General admission requirements

Degree-specific requirements: Science

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