Subject
Subject: Mathematics
Grade: 12
Credits:1.0
Type: University Preparation
Language of Study: English
Course description: Learn more about mathematics for managing data. Organize and analyze information, solve probability problems, and carry out a culminating investigation that integrates statistical concepts and skills. Preview Course
Interested in taking this course?
- If you are a student already enrolled in an Ontario High School, please contact your school about taking courses with TVO ILC.
- If your goal is to earn a high school diploma or if you are a homeschool student, an academic assessment of your application must be done before choosing courses, please visit Apply Now to start your application.
Grade: 12
Credits:1.0
Type: University Preparation
Language of Study: English
Course description: Learn more about mathematics for managing data. Organize and analyze information, solve probability problems, and carry out a culminating investigation that integrates statistical concepts and skills. Preview Course
Course fees are partially subsidized for most Ontario residents. The administrative fee covers the cost for us to process your application.
Interested in taking this course?
- If you are a student already enrolled in an Ontario High School, please contact your school about taking courses with TVO ILC.
- If your goal is to earn a high school diploma or if you are a homeschool student, an academic assessment of your application must be done before choosing courses, please visit Apply Now to start your application.
Course Overview
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 Syllabus
This course is designed for independent study. Our courses are routinely reviewed for errors and adherence to AODA accessibility standards. We appreciate your patience as we work towards delivering high-quality digital learning for all.
This course is designed for independent study. Our courses are routinely reviewed for errors and adherence to AODA accessibility standards. We appreciate your patience as we work towards delivering high-quality digital learning for all.
To preview the lessons, please visit this page with a computer or tablet.
22 Lessons
1.1
Introducing the Importance of Data
1.1
Introducing the Importance of Data
1.2
Recognizing Bias Data Collection Principles and Methods
1.2
Recognizing Bias Data Collection Principles and Methods
1.3
Analyzing Two Variable Data
1.3
Analyzing Two Variable Data
1.4
Analyzing the Residuals and Outliers in Two Variable Data
1.4
Analyzing the Residuals and Outliers in Two Variable Data
1.6
Interpreting Data
1.6
Interpreting Data
2.1
Introducing One Variable Statistics
2.1
Introducing One Variable Statistics
2.2
Calculating Measures of Central Tendency
2.2
Calculating Measures of Central Tendency
2.3
Calculating Measures of Spread
2.3
Calculating Measures of Spread
2.5
Learning About Normal Distribution and Z-Scores
2.5
Learning About Normal Distribution and Z-Scores
2.6
Applying Z-Scores to Discrete Data
2.6
Applying Z-Scores to Discrete Data
2.7
Exploring Confidence Intervals
2.7
Exploring Confidence Intervals
3.1
Introducing Organized Counting and the Fundamental Multiplicative Counting Principle
3.1
Introducing Organized Counting and the Fundamental Multiplicative Counting Principle
3.2
Learning about Permutations Factorials: Rule of Sum and Applications
3.2
Learning about Permutations Factorials: Rule of Sum and Applications
3.3
Understanding Combinations
3.3
Understanding Combinations
3.5
Counting Problems with Repeated Elements and Overlap
3.5
Counting Problems with Repeated Elements and Overlap
3.6
Investigating Pascal Triangle and Problems using Combinations
3.6
Investigating Pascal Triangle and Problems using Combinations
4.1
Introducing Experimental vs Theoretical Probability
4.1
Introducing Experimental vs Theoretical Probability
4.2
Learning About Mutually Exclusive and Non-Mutually Exclusive Events
4.2
Learning About Mutually Exclusive and Non-Mutually Exclusive Events
4.3
Understanding Independent and Dependent Events
4.3
Understanding Independent and Dependent Events
4.5
Exploring Probability Distributions and Expected Value
4.5
Exploring Probability Distributions and Expected Value
4.6
4.6 Calculating Binomial Distribution and Hypergeometric Distribution
4.6
4.6 Calculating Binomial Distribution and Hypergeometric Distribution
4.7
Applying Normal Approximation to the Binomial Distribution
4.7
Applying Normal Approximation to the Binomial Distribution