Course name: Mathematics of Data Management Course code: (MDM4U)

Grade 12    1.0 Credit

Course type:    University Preparation

Course description: This course will broaden your understanding of mathematics as it relates to managing data. You 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. You will also refine your use of the mathematical processes necessary for success in senior mathematics. If you are planning to enter university programs in business, the social sciences, and the humanities you will find this course of particular interest.
MDM4UJ: Mathematics of Data Management
Course description: This course will broaden your understanding of mathematics as it relates to managing data. You 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. You will also refine your use of the mathematical processes necessary for success in senior mathematics. If you are planning to enter university programs in business, the social sciences, and the humanities you will find this course of particular interest.

Course Lessons

This course is designed for independent study.
This course is designed for independent study. To review the lessons, please visit this page with a computer or tablet.
22 Lessons

5 Lessons

1.1   Introducing the Importance of Data

1.2   Recognizing Bias Data Collection Principles and Methods

1.3   Analyzing Two Variable Data

1.4   Analyzing the Residuals and Outliers in Two Variable Data

1.6   Interpreting Data

6 Lessons

2.1   Introducing One Variable Statistics

2.2   Calculating Measures of Central Tendency

2.3   Calculating Measures of Spread

2.5   Learning About Normal Distribution and Z-Scores

2.6   Applying Z-Scores to Discrete Data

2.7   2.7 Exploring Confidence Intervals

5 Lessons

3.1   Introducing Organized Counting and the Fundamental Multiplicative Counting Principle

3.2   Learning about Permutations Factorials: Rule of Sum and Applications

3.3   Understanding Combinations

3.5   Counting Problems with Repeated Elements and Overlap

3.6   Investigating Pascal Triangle and Problems using Combinations

6 Lessons

4.1   Introducing Experimental vs Theoretical Probability

4.2   Learning About Mutually Exclusive and Non-Mutually Exclusive Events

4.3   Understanding Independent and Dependent Events

4.5   Exploring Probability Distributions and Expected Value

4.6   Calculating Binomial Distribution and Hypergeometric Distribution

4.7   Applying Normal Approximation to the Binomial Distribution