MDM4U – Mathematics of Data Management – Grade 12 Handouts & Resources

MDM4U Grade 12 Data Management Math Course Description

MDM4U Grade 12 Data Management MathematicsThis 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 few years. 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.

It should also be noted that I have undergone a complete transformation in how I believe mathematics should be taught and learned and thus how I delivered math lessons a decade ago is completely different than how I teach now. Learn more about transforming your math lessons from rushing to procedures to problem based math lessons here.


3 Act Math Tasks

MDM4U Grade 12 Data Management Real World Math Problems


Candle's Burning 3 Act Math Task Data PointsAccess 3 Act Math Tasks related to the MDM4U Grade 12 Data Management Math Course.

Access Grade 12 Data Management course material related to Counting and Probability, Data Management and Statistical Analysis.


MDM4U 3 Act Tasks

There may also be some 3 act math style problem based lessons and units on the Make Math Moments site.


MDM4U Grade 12 Data Management Culminating Projects

Statistics and Probability Independent Projects


MDM4U Grade 12 Data Management Culminating ProjectAccess the MDM4U Grade 12 Data Management Culminating Project Expectations, Rubric, Proposal and Exemplars for both the One- and Two-Variable Statistics and Probability Culminating Projects.


Culminating Projects


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
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
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
Page 449-450 #1-7

MDM4U Grade 12 Mathematics of Data Management

Strands and Overall Expectations


Counting and Probability

Probability Distributions

  • PD1 – 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;
  • PD2 – 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

Statistical Analysis

Culminating Data Management Investigation

  • CI1 – 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;
  • CI2 – communicate the findings of a culminating investigation and provide constructive critiques of the investigations of others.