MDM4U Grade 12 Data Management Math Course Description
This course broadens students’ understanding of mathematics as it relates to managing data. Students will apply methods for organizing and analysing large amounts of information; solve problems involving probability and statistics; and carry out a culminating investigation that integrates statistical concepts and skills. Students will also refine their use of the mathematical processes necessary for success in senior mathematics. Students planning to enter university programs in business, the social sciences, and the humanities will find this course of particular interest.
Prerequisite: Functions, Grade 11, University Preparation, or Functions and Applications, Grade 11, University/College Preparation
I often receive emails from teachers across Ontario looking for some resources for the Grade 12 MDM4U Data Management course. I always loved teaching this course, but haven’t had the opportunity in the past year. Take what you’d like from here. If it helps you along the way, I’d love to hear from you in the comments section at the bottom of the page.
MDM4U – Mathematics of Data Management – Grade 12 – Worksheets
McGraw-Hill Ryerson – Digital Textbook
| RESOURCES | DESCRIPTION |
| Electronic Textbook & Full Solutions Manual |
McGraw-Hill Ryerson Textbook: Mathematics of Data Management in PDF format. Also included is the full solution manual for even numbered problems.Download Adobe Reader to view files. All files are numbered according to the order of the textbook, not our course! |
| Introduction to Excel | Powerpoint presentation which teaches the user, step-by-step, how to use Microsoft Excel to manage and manipulate data effectively. |
| Introduction to Fathom | Powerpoint presentation which teaches the user, step-by-step, how to use Fathom to manage and manipulate data effectively. |
| Importing Data Into Fathom | Word document which describes how to import data into Fathom and other data management software packages. |
MDM4U – Unit 1 – Statistics of One Variable
| Sec. 1.1 (2.1) – Data Analysis with Graphs (Part 1) | Page 101-103 #2, 7, 13 |
| Sec. 1.1 (2.1) – Data Analysis with Graphs (Part 2) | Page 101-103 #1, 3(ab), 5, 9, 11 |
| Sec. 1.2 (2.3) – Sampling Techniques | Page 117-118 #1-9 |
| Sec. 1.3 (2.4) – Bias (Learn Independently) | Page 123-124 #1-6, 8 |
| Sec. 1.4 (2.5) – Measures of Central Tendency | Page 133-135 #1-10, 12, 14 |
| Sec. 1.5 (2.6) – Measures of Spread (Part 1) | Page 148-150 #1, 6a, 10 |
| Sec. 1.5 (2.6) – Measures of Spread (Part 2) | Page 148-150 #2-5, 6bc, 9, 11-14 |
MDM4U – Unit 2 – Statistics of Two Variables
| Sec. 2.1 (3.1) – Scatter Plots and Linear Correlation | Page 168-170 #1-3,5,6,9,10 |
| Sec. 2.2 (3.2) – Linear Regression | Page 180-183 #1,2,5-7,14 |
| Sec. 2.3 (3.4) – Cause and Effect | Page 199-201 #1-5, 8, 11, 14 |
| Sec. 2.4 (3.5) – Bias (Learn Independently) | Page 209-211 #1-5,8 |
MDM4U – Unit 3 – Organized Counting
| Sec. 3.1 (4.1) – Organized Counting | Page 229 #1-20 |
| Sec. 3.2 (4.2) – Factorial Notation | Sec. 3.2 Handout |
| Sec. 3.3 (4.2) – Counting Permutations | Page 239 #1-4, 6ab, 7, 9-16, 19, 22 |
| Sec. 3.4 (4.3) – Permutations with Some Identical Elements (Learn Independently) | Page 245 #2-5, 7-9, 12, 13 |
| Sec. 3.5 (4.4 & 4.5) – Pascal’s Triangle | Page 251 #2-4 & Page 256 #1-11 |
MDM4U – Unit 4 – Combinations
| Sec. 4.1 (5.1) - Counting with Set Theory and Venn Diagrams | Page 170-172 #1-9 |
| Sec. 4.2 (5.2) – Combinations | Page 179-181 #1-9, 11-15 |
| Sec. 4.3 (5.3) – Problem Solving with Combinations | Page 286-287 #1-13 |
| Sec. 4.4 (5.4) – Relating Pascal’s Triangle to Combinations | Page 193 #1 and 4.4.1 & 4.4.2 Worksheets |
MDM4U – Unit 5 – Probability
| Sec. 5.1 (6.1) – Introduction to Probability (Part 1) | Page 312-313 #1, 4, 5, 6, 11 |
| Sec. 5.1 (6.1) – Introduction to Probability (Part 2) | Page 312-313 #2, 3, 7, 10 |
| Sec. 5.2 (6.2) – Odds | Page 318-319 #1-6, 9-12 |
| Sec. 5.3 (6.3) – Problem Solving Using Counting Techniques | Page 324-326 #1-11 |
| Sec. 5.4 (6.4) – Dependent and Independent Events | Page 334-335 #1-10, 1 |
| Sec. 5.5 (6.5) – Mutually Exclusive Events (Learn Independently) | Page 340-343 #1-8, 11, 13 |
MDM4U – Unit 6 – Discrete Probability Distributions
| Sec. 6.1 (7.1) – Probability Distributions | Page 374-376 #1-13 |
| Sec. 6.2 (7.2) – Binomial Distribution | Page 385-387 #1, 2a, 3, 5, 6bc, 7, 8ab, 10, 11 |
| Sec. 6.3 (7.3) – Geometric Distribution | Page 394-396 #1-12 |
| Sec. 6.4 (7.4) – Hypergeometric Distribution | Page 404-405 #1, 2a, 3, 7-12 |
MDM4U – Unit 7 – The Normal Distribution
| Sec. 7.1.1 (8.1) – Continuous Probability Distributions | Page 419-421 #1-4, 6 |
| Sec. 7.1.2 (8.1) – Continuous Probability Distributions (Cont…) | Page 420-421 #7,9 & 7.1.2 Worksheet |
| Sec. 7.2 (8.2) – Properties of the Normal Distribution | Page 430-431 #1-10 |
| Sec. 7.3 (8.3) – Normal Sampling and Modelling | Page 439-441 #1-3, 8-10 |
| Sec. 7.4 (8.4) – Normal Approximation to the Binomial (Learn Independently) | Page 449-450 #1-7 |
About Kyle Pearce
Secondary Math Teacher and Intermediate Math Coach with the Greater Essex County District School Board leading a Ministry funded 1:1 iPad project called Tap Into Teen Minds. I currently teach at Tecumseh Vista Academy K-12 in the morning and focus on duties for the Middle Years Collaborative Inquiry (MYCI) Project in the afternoon.
