Mathematics and Statistics

Mathematics is one of the oldest sciences. Although there are many applications of mathematics, the subject seeks to resolve questions whose answers will deepen our understanding of, and reveal new insights into, mathematics itself. The inherent structure and elegance of mathematics are features of the subject that are difficult to surpass in other sciences.

Mathematics also differs from other disciplines in that its advances come through the application of pure reason (by way of the human mind) rather than through observation (by way of scientific instrumentation). Consequently, mathematics builds upon its past achievements and develops independently of technological advancements.

Statistics is a data-driven science about how numbers help us understand the world, predict future events, and analyze information.

At the U of R, you can take one of eight bachelor's degree programs in mathematics and statistics as well as a certificate:

Bachelor of Science in Mathematics

In this program, you will learn to be proficient in the uses of mathematics, especially calculus, matrix algebra, and differential equations. You will also be exposed to statistics, computer science, and higher level mathematical reasoning in the form of mathematical proof. Courses in number theory, abstract algebra, and optimization can be taken as part of this program.

Bachelor of Science Honours in Mathematics

In the honours program, you will learn to be proficient in high level abstract mathematical reasoning. The honours program is excellent preparation for graduate studies; many University of Regina graduates from the program go on to earn MSc and PhD degrees at top universities in North America.

Bachelor of Science in Statistics

In this program you will take courses in statistics and probability, as well as theoretical and applied courses. Statisticians at the bachelor of science level are needed in industry, government, and academics (colleges, technical schools). The Bachelor of Science in Statistics is also a pathway to graduate studies, which can lead to a variety of skilled careers such as a statistician or data scientist.

Bachelor of Science Honours in Statistics

In the honours program, you will learn to be proficient in high level statistical reasoning that prepares you for careers in the non-academic sector and for continued studies at the masters and doctoral level.

Bachelor of Science in Applied Mathematics and Statistics

Graduates of this program will be proficient in the uses of mathematics, especially calculus, matrix algebra, differential equations, probability, and statistics. You will also be exposed to computer science and higher level mathematical reasoning in the form of mathematical proofs.

Bachelor of Science in Data Science

The modern world uses data in an unprecedented way, and there is a great demand for people with skills on how to manage, understand, and apply large data sets. The new data science program (which is offered jointly with the Department of Computer Science) is designed so that students with good math skills can use a blend of mathematical, statistical, and computational science for the analysis, interpretation, and application of data.

Bachelor of Science in Statistics and Economics (combined major)

The combined degree in Statistics and Economics is designed for students with an interest in both fields. This program provides a broad understanding of the fundamental concepts involved in both subjects.

Bachelor of Science in Computer Science and Math (combined major)

This program is designed for students who are interested in computation or theoretical computer science.

Certificate in Statistics

The two-year certificate is ideal for students who are majoring in another subject, but wish to acquire this formal credential to recognize their foundational knowledge of statistics. Because of the prerequisite structures of the program, the certificate requires at least four semesters to complete. Completion of the certificate can be a ladder into the Bachelor of Science in Statistics.

What are Mathematics, Applied Mathematics and Statistics?

Mathematics

Mathematics is the science that deals with the logic of shape, quantity and arrangement. It is the building block for nearly everything in our daily lives, including smartphones, computers, software, architecture (ancient and modern), art, money, engineering, travel, and sports.

The main branches of pure mathematics are:

• Algebra (the study of arithmetical systems of various types)

• Analysis (the study of the continuum and the mathematics of change)

• Combinatorics (the mathematics of counting)

• Probability (the mathematics of random phenomena)

• Topology (the study of geometrical objects and their deformations)

Applied Mathematics & Statistics

In applied mathematics, the development of mathematical tools is the main objective. Some examples are:

• The study of how blood flows through the cardiovascular system

• Number-theoretic encryption for secure internet commerce

• The development of models for understanding the folding process in proteins

Applied mathematics also involves a strong knowledge of statistical science, which is fundamental to analyzing and interpreting data.

Statistics

Statistics is an academic subject that collects data for research purposes and provides theories and methods to analyze data and make scientific judgments about uncertain outcomes of interest. Statistical models and methods have applications in almost all industries and academic research disciplines that seek meaningful results from data. Here are a few examples of practical projects:

• Predict full season results of Major League Baseball players based on their historical performance measures (e.g., hitting averages)

• Classify customers based on spending behaviour (e.g., the number of shops to use, the average time to spend in a shop, the average amount to spend, etc.)

• Predict whether someone will have a certain type of cancer on the basis of demographic, diet and clinical measurements

• Identify the economic impact of epidemic animal diseases and their control programs

The rapid development and increased use of information and communication technologies produce a vast amount of data that can be used for many purposes. Recently, there has been an increased demand for statistical specialists, such as statisticians or data scientists, who analyze and use large amounts of data.

Some specialty courses in math and statistics at the U of R include:

Introduction to Quantum Information Theory

Introduction to Quantum Information Theory is a course in the mathematics of quantum information theory. Topics include information measures, quantum states and observables, qubits, entanglement, quantum channels, entropy, and measurements.

Introduction to Statistical Inference

Introduction to Statistical Inference includes sampling distribution theory and the central limit theorem; large sample theory; methods of estimation and hypothesis testing including maximum likelihood estimation, likelihood ratio testing, and confidence interval construction.

Statistical Learning and Predictive Modeling

Statistical Learning and Predictive Modeling examines selected topics and techniques in statistical learning and predictive modeling, including linear models, logistic regression models, regression trees, classification models and statistical software.

A graduating average of at least 70 per cent from a four-year baccalaureate degree (or equivalent) is required for admission to all programs except for English, History, Mathematics and Statistics and the Master of Public Administration where the required average is 75 per cent.

Applicants with a marginally lower four-year average may be accepted if their performance in the last two complete years is significantly higher (75 per cent or more).

Applicants must have the academic background required to undertake graduate studies in their chosen field. Applicants who fail to meet this requirement but who otherwise meet the criteria may be admitted; however, background deficiencies must be addressed by taking appropriate courses either prior to or in parallel with graduate work.