Mathematics of Data Management

MDM4U focuses on data analysis, probability, and statistical reasoning to help students make informed decisions in personal, academic, and professional contexts.

Through hands-on investigations and real-world data, students learn how to collect, organize, and interpret information.

This course builds foundational skills in probability theory and statistical modelling—essential for future studies in business, social sciences, biology, and related fields.

Unit 1: Introduction to Statistics and Data
Students develop core skills for analyzing and interpreting data.
Lessons include:

• Bias in Sampling Methods
• Measures of Central Tendency
• Visual Data Displays
• Scatter Plots and Correlation
• Linear Regression and Bivariate Data
• Z-Scores and Standardization

Unit 2: Counting and Probability
This unit introduces foundational principles of probability.
Lessons include:

• Basic Probability Rules
• Events and Their Dependency
• Counting Principles (Permutations & Combinations)
• Applying Probability to Real Situations

Unit 3: Probability Distributions
Students explore how data can be modeled using different distributions.
Lessons include:

• Probability Distribution Fundamentals
• Binomial and Hypergeometric Distributions
• Continuous and Normal Distributions
• Applications of Z-scores and Probability Models

Unit 4: Data Organization and Surveys
This unit focuses on designing and analyzing data collection tools.
Lessons include:

• Types of Statistical Data
• Data Collection Methods
• Survey Design and Reliability
• Variability, Outliers, and Sampling Strategies

Unit 5: Culminating Project and Report Writing
Students apply course concepts in an independent investigation.
Lessons include:

• Defining a Research Problem
• Creating an Action Plan
• Collecting and Analyzing Data
• Writing and Presenting a Final Report

Unit 6: Final Evaluation
Students complete a formal report and exam.
Lessons include:

• Culminating Project Report
• Final Exam

• 70% of the final grade is based on coursework, including:
  • Statistical analysis assignments
  • Data interpretation and survey critique
  • Probability modeling tasks
  • Quizzes, discussions, and unit tests
• 30% of the final grade is based on final evaluations:
  • 10% Independent culminating data project
  • 20% Final exam testing statistical understanding and probability applications

All assessments follow Ontario curriculum standards and are designed to build real-world data literacy, statistical reasoning, and decision-making confidence.