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MDM4U Mathematics Of Data Management – Grade 12 (University)

  • Grade 12

PREREQUISITE: Functions, Grade 11, University Preparation, or Functions and Applications, Grade 11, University/College Preparation

GRADE: 12 (University)

AVAILABILITY: Full-time – All Campuses, Part-time – All campuses, Private – All campuses, Blyth Academy Online


Course Overview

MDM4U online broadens students’ understanding of mathematics as it relates to managing information. Students will apply methods for organizing large amounts of information; solve problems involving counting techniques, probability, and statistics; and carry out a culminating project that integrates the expectations of the course. Students will continue to develop the mathematical processes necessary for success in senior mathematics. Students planning to pursue university programs in business, the social sciences, and the humanities will find MDM4U online of particular interest. Whether you take the mathematics of data management course online or on campus, it will prepare you for the next steps in a university program and in your future career.

Course Outline

Below is a course outline for the MDM4U course. This data management grade 12 course outline is the same whether you take the course in person or online. The curriculum is set by Ontario’s Ministry of Education, so all students who take MDM4U, regardless of setting, can expect to gain skills in mathematics and data management.

The overarching aim of MDM4U is to help students fluidly use the language of mathematics while honing their skills for managing data and performing mathematical processes. The course explores concepts and skills involving probability and statistics and helps students gain confidence with analyzing large amounts of data. To accommodate various learning styles, ability levels, and interests, the course utilizes an array of instructional strategies.

Permutations and Combinations

Essential Question: How can counting principles be used to predict the number of arrangements possible in a real-world counting scenario?

In this unit, students will explore the fundamental counting principle and apply it to solve real-world counting problems. Students will explore the factorial operation and apply it to develop an understanding of permutations and combinations. Lastly, students will make connections between their developing understanding of counting techniques and Pascal’s Triangle, another valuable tool for solving real-world counting problems.


Essential Question: How can we use our understanding of probability to communicate the likelihood of real-world scenarios occurring?

In this unit, students will explore the fundamental difference between experimental and theoretical probabilities using real-world examples to make comparisons. Students will then combine their understanding of permutations and combinations with their understanding of probability concepts to solve problems involving probabilities and counting arrangements.

Discrete Probability Distributions

Essential Question: How can an understanding of probability distributions be used to make real-world predictions?

In this unit, students will explore a variety of types of distributions of data and make comparisons between their key characteristics. Students will apply their understanding of uniform, binomial, and hypergeometric distributions to solve expected value problems and represent data graphically on histograms.

Collecting Data

Essential Question: How can sources of bias influence data collection and the conclusions formed by data collectors as a result?

In this unit, students will explore strategies for collecting data which can be used to form valid and reliable conclusions. Students will learn how to write unbiased survey questions and investigate different sampling techniques. Lastly, students will learn how to represent collected data visually using technology.

Continuous Probability Distributions

Essential Question: Why do specific patterns exist in certain sets of data?

In this unit, students will revisit the concepts of measures of central tendency. This will serve as a foundation for further studies into measures of spread and standard deviation as a means of analyzing a single variable. The normal distribution and z-scores will be introduced and comparisons will be made between binomial and normal distributions using normal approximation.

Two-Variable Statistical Analysis

Essential Question: Does correlation always imply causation?

In this unit, students will explore the tools available for assessing the strength of the correlation between two variables. Students will perform linear regression analyses using technology, and think critically to determine if a change in one variable causes a change in another.


Overall, course evaluation is based on a student’s achievement of curriculum expectations as well as skills demonstrated for effective learning. The final percentage grade received upon completion of the MDM4U course reflects the quality of how a student has achieved course expectations. The final grade is broken down as follows:

70% of the grade: Based on evaluations conducted throughout the course, this part of the grade reflects the most consistent level a student achieves for the duration of the course. Special consideration may be given to recent evidence of improved achievement.

30% of the grade: Based on final evaluations conducted at the conclusion of the course, the final assessment includes a culminating project and a final exam. The culminating project represents 10% of the overall final grade, while the final proctored exam represents 20% of the overall final grade. The culminating project and final proctored exam are described below.

Please consult our Frequently Asked Questions Page or the Exam section within your course for more details on final exams and the exam fee. More information can also be found in our Student Handbook
Ready to get started? Register today

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