Inspiring Passion For Learning
905-683-1610
Course, Grade, and Level: Mathematics of Data Management, Grade 12, University
Preparation (MDM4U) Credit Value: 1.0 Prerequisites: MCF3M, MCR3U
Date Revised: June 26, 2013
Curriculum Document: (The Ontario Curriculum, Grade 9-12, Mathematics, 2007)
Teacher and Voicemail: (Mr. Bentley, x1205
Department and Head: Mathematics, Ms. Fu
Overall Course Expectations:
Counting and Probability
By the end of this course, students will:
solve problems involving the probability of an event or a combination of events for discrete sample spaces;
solve problems involving the application of permutations and combinations to determine the probability of
an event.
Probability Distributions
By the end of this course, students will:
demonstrate an understanding of discrete probability distributions, represent them numerically, graphically,
and algebraically, determine expected values, and solve related problems from a variety of applications;
demonstrate an understanding of continuous probability distributions, make connections to discrete
probability distributions, determine standard deviations, describe key features of the normal distribution,
and solve related problems from a variety of applications.
Organization of Data for Analysis
By the end of this course, students will:
demonstrate an understanding of the role of data in statistical studies and the variability inherent in data,
and distinguish different types of data;
describe the characteristics of a good sample, some sampling techniques, and principles of primary data
collection, and collect and organize data to solve a problem.
Statistical Analysis
By the end of this course, students will:
analyse, interpret, and draw conclusions from one-variable data using numerical and graphical summaries;
analyse, interpret, and draw conclusions from two-variable data using numerical, graphical, and algebraic
summaries;
demonstrate an understanding of the applications of data management used by the media and the
advertising industry and in various occupations.
Culminating Data Management Investigation
By the end of this course, students will:
design and carry out a culminating investigation that requires the integration and application of the
knowledge and skills related to the expectations of this course;
communicate the findings of a culminating investigation and provide constructive critiques of the
investigations of others.
Course Content and Topics:
Unit 1 Probability
Unit 2 Permutations and Combinations
Unit 3 Organization of Data for Analysis
Unit 4 Statistics
Unit 5 Probability Distributions of Discrete Random Variables
Unit 6 Continuous Data
Teaching strategies may include, but are not limited to the following:
 Concept / Mind Mapping
 Demonstration / Modeling
 Compare / Contrast
 Summarizing / Note-taking
 Cooperative Learning
 Problem Solving
 Independent Study
 Inquiry-based Learning
Assessment and Evaluation:
Each course is evaluated on the basis of the following four categories of achievement:
Assessment:
Knowledge/Understanding
Application
Thinking
Communication
35%
35%
15%
15%
Evaluation:
Term Work: 70%
Summative Evaluation: 30%
Learning Skills: All students will be assessed on the following learning skills: Responsibility,
Independent Work, Initiative, Organization, Collaboration, and Self-regulation. The categories
for assessment are: Excellent, Good, Satisfactory or Needs Improvement
“Programming and assessment for exceptional learners will be an ongoing and continuous
process that is an integral part of the learning process.” (Growing Success, 2010)
Textbook and Course Materials: A textbook will be assigned to each student. The
textbook is: "McGraw-Hill Ryerson MATHEMATICS of DATA MANAGEMENT". The
replacement cost of this textbook is $100.00 and $10.00 for the course disk. If the
student returns a damaged textbook / disk at the end of the semester, a damage fee will
be levied.
Other Requirements: It is important that each student keep a complete, organized set
of notes that is suitable for his/her study needs. It is the students responsibility to have
the following materials for each class:
3-ring binder and looseleaf paper,
a duotang for your journal, which will be left in the classroom,
pencils / pens, eraser, ruler,
a scientific calculator with factorial functions,
graph paper
LATE AND/OR MISSED ASSESSMENT TASKS
It is the student’s responsibility to review school and subject department assessment and evaluation
policies/procedures carefully. It is the student’s responsibility to complete all assessment opportunity
tasks (projects, assignments, presentations, etc.) by the due date assigned by the teacher.
If the student is unable to complete a task due to insufficient knowledge or skills, it is the student’s
responsibility to seek assistance from the teacher well in advance of the due date for the task.
Some task due dates are negotiable, some are absolute and non-negotiable (e.g., some Independent
Study Unit/Major Project). If a student is unable to complete a task by a due date, it is the student’s
responsibility to discuss the reason(s) with the teacher, prior to the due date.
If the student does not submit or complete assigned tasks, for either the negotiated or absolute due
dates, that work may not be assessed/evaluated, a mark penalty may be imposed and/or the student
may receive a mark of zero.
If there is a mark penalty, it will be imposed as follows:


10% of the value of the assignment will be deducted for the first day
5% of the value for each subsequent day, until such time as the teacher determines a mark of
zero should be applied.
 a weekend will be deemed as one day.
(Example: an assignment that receives a mark of 85% but is one day late will receive a mark of 75%)
Some due dates cannot be changed (eg. end of unit or term, mark reporting deadlines). If
assessment tasks are not completed, course expectations can not be evaluated, and a mark of zero
may be assigned.
Please also refer to the Assessment and Evaluation section of the Student Code of Conduct.