The MDM4U online course is designed to expand students’ mathematical knowledge with a focus on data analysis and real-world application. Students learn to organize and interpret large datasets, solve problems using probability and statistics, and complete a culminating investigation that integrates key concepts. This course strengthens essential math skills for senior-level success while preparing students for university programs in business, social sciences, and humanities, bridging the gap between theory and practical application.
Course curriculum
Inside %course-code%: making sense of data
The math credit for business and social science
Students planning to enter university programs in business, the social sciences and the humanities will find this course of particular interest — it satisfies a Grade 12 U math requirement without calculus.
Probability, from counting to distributions
Permutations, combinations and Pascal’s triangle, then discrete and continuous probability distributions — binomial, hypergeometric and normal — with expected value.
Statistics you can stand behind
Sampling, bias and survey design, measures of central tendency and spread, correlation and regression, and how to judge whether a study’s conclusions hold up.
Working with real data
Collect and organize data, choose the right way to display it, and analyse one- and two-variable data sets — the methods for handling large amounts of information the course is built around.
Interactive simulations — see the statistics
Simulations for independent and dependent events, histograms, and correlation and regression let you generate and play with data as you learn, and a question-and-answer conversation with your teacher in each unit checks your reasoning along the way.

MDM4U Course outline
Full unit-by-unit breakdown.
Solve probability problems involving discrete sample spaces, and problems using counting principles — fundamental counting, permutations and combinations — including dependent, independent and mutually exclusive events.
Key topics
Probability basics · fundamental counting techniques · permutations · Pascal’s triangle and combinations · dependent, independent and mutually exclusive events
Assessed by
Combinations quiz · question-response conversation · proctored unit test
Explore and understand probability distributions for discrete and continuous random variables and their expected values.
Key topics
Discrete probability distributions and expected value · binomial distribution · hypergeometric distribution
Assessed by
Unit assignment · question-response conversation · proctored unit test
Explore data concepts, then collect and organize data: types of data and sampling, bias and surveys, and displaying and organizing results.
Key topics
Types of data and sampling · bias and surveys · displaying and organizing data · histograms
Assessed by
Bias and surveys quiz · question-response conversation · proctored unit test
Analyse one-variable and two-variable data, from measures of central tendency and spread to the normal distribution and regression, and evaluate the validity of a study.
Key topics
Measures of central tendency · standard deviation and variance · normal distribution · quartiles and percentiles · correlation and regression
Assessed by
Unit assignment · question-response conversation · proctored unit test
Review the four units and prepare for the cumulative final exam.
Key topics
Course review
Assessed by
Final exam
