Course Title: Mathematics of Data Management
Course Code: MDM4U
Grade: 12
Course Type: University Preparation
Credit Value: 1
Prerequisite: MCR3U, Functions, Grade 11, University Preparation or MCF3M, Functions and Applications, Grade 11, University / College Preparation
Department: Mathematics

Course Description

This course broadens students’ understanding of mathematics relating to the management 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.

Course Outline
  • MDM4U Unit1 Overview
  • Accessibility to MDM4U Unit1 Assignment
  • U1L1 Iterative process (A1.4)
  • U1L2 Data management systems (A1.4)
  • U1L3 Modelling in softwares (A1.4)
  • U1L4 Database and types of data (C1.1)
  • U1L5 Concepts and application of simulations (C1.2)
  • U1L6 Interpret results of simulations (C1.3)
  • U1L7 Concepts of Graph Theory (B2.5)
  • U1L8 Application of Graph Theory (B2.5)
  • U1L9 Utilization of network systems in data collection (C2.5)
  • U1L10 Data collection in the form of matrices (C2.1)
  • U1L11 Matrix properties and operations (Part 1) (C2.1)
  • U1L12 Matrix properties and operations (Part 2) (C2.1)
  • U1L13 Concepts of statistics (D1.3)
  • U1L14 Graph representations (D1.5)
  • U1L15 Population and Sample (D1.5)
  • U1L16 Population and Sample (B2.4 C2.4)
  • U1L17 Sampling techniques (B2.3)
  • U1L18 Bias in a survey (C2.3)
  • U1L19 Central tendency (D1.1)
  • U1L20 Measures of spread (D1.2)
  • U1L21 Quartiles, Percentiles, and Z-Scores (D1.4)
  • U1L22 Matrix in problem solving (C2.2)
  • U1L23 Complex matrix operations (C2.2)
  • U1L24 Differences and similarities of various sampling techniques (C2.4)
  • Finish and hand in MDM4U Unit1 Assignment at the end of lesson
  • MDM4U Unit2 Overview
  • Accessibility to MDM4U Unit2 Assignment
  • U2L1 Two-variable data (D2.3)
  • U2L2 Linear regression (D2.4)
  • U2L3 Non-linear regression (D2.5)
  • U2L4 Cause and effect (D2.1)
  • U2L5 Correlation of 2-variable date (D2.2)
  • U2L6 Validity of statistical conclusions (D3.2)
  • U2L7 Concepts of counting principles (A2.1)
  • U2L8 Applications of counting principles (A2.1)
  • U2L9 Basic concepts of combinations and permutations (A2.1 A2.2)
  • U2L10 Permutation (A2.3)
  • U2L11 Permutations with identical items (Part 1) (A2.3)
  • U2L12 Permutations with identical items (Part 2) (A2.3)
  • U2L13 Pascal’s Triangle (A2.3)
  • U2L14 Pascal’s Triangle – application (Part 1) (A2.3 A2.4)
  • U2L15 Pascal’s Triangle – application (Part 2) (A2.3 A2.4)
  • U2L16 Venn Diagrams (A2.3)
  • U2L17 Combination (A2.4)
  • U2L18 Problem Solving with Combinations (Part 1) (A2.4)
  • U2L19 Problem Solving with Combinations (Part 2) (A2.4)
  • U2L20 The Binomial Theorem (Part 1) (A2.4)
  • U2L21 The Binomial Theorem (Part 2) (A2.4)
  • U2L22 Combinations and permutations (A2.2)
  • U2L23 Interpret statistics presented in the media (D3.1)
  • U2L24 Real word examples (D3.1)
  • Finish and hand in MDM4U Unit2 Assignment at the end of lesson
  • MDM4U Unit3 Overview
  • Accessibility to MDM4U Unit3 Assignment
  • U3L1 Concepts of probability (A1.1)
  • U3L2 Probability and statistics (A1.1)
  • U3L3 Probability in terms of odds (A1.1)
  • U3L4 Probability and counting principles (A1.2)
  • U3L5 Probability and counting principles – application (A1.2)
  • U3L6 Dependent, independent, and conditional events (A1.3)
  • U3L7 Mutually exclusive events (A1.5)
  • U3L8 The law of total probability (A1.5)
  • U3L9 Markov process (A1.6)
  • U3L10 Probability distribution (B1.3)
  • U3L11 Discrete and continuous random variables (B1.3)
  • U3L12 Expectation of a random variable (B1.3)
  • U3L13 Binomial distribution (Part 1) (B1.4)
  • U3L14 Binomial distribution (Part 2) (A1.4)
  • U3L15 Bernoulli trials (B1.4)
  • U3L16 Geometric distribution (Part 1) (B1.5)
  • U3L17 Geometric distribution (Part 2) (B1.5)
  • U3L18 Hypergeometric Distributions (Part 1) (B1.5)
  • U3L19 Hypergeometric Distributions (Part 2) (B1.6)
  • U3L20 Probability distributions of discrete random variables (Part 1) (B1.6)
  • U3L21 Probability distributions of discrete random variables (Part 2) (B1.6)
  • U3L22 Independent and dependent events (A1.6)
  • U3L23 Combinations to solve probability problems (A2.5)
  • U3L24 Pascal’s Triangle (A2.5)
  • Finish and hand in MDM4U Unit3 Assignment at the end of lesson
  • MDM4U Unit4 Overview
  • Accessibility to MDM4U Unit4 Assignment
  • U4L1 Discrete distribution and continuous distribution (Part 1) (B1.1)
  • U4L2 Discrete distribution and continuous distribution (Part 2) (B1.1 B1.2)
  • U4L3 Exponential distribution (B1.1)
  • U4L4 Normal distribution (B2.6)
  • U4L5 z-table (B2.6)
  • U4L6 Normal sampling and modelling (B2.6)
  • U4L7 Application of normal distribution (B2.7)
  • U4L8 Use normal distribution to approximate binomial distribution (B2.7)
  • U4L9 Fit a normal distribution to any probability distribution (B2.8)
  • U4L10 Repeated sampling (B2.1)
  • U4L11 Hypothesis testing (B2.1)
  • U4L12 Confidence intervals (B2.2)
  • U4L13 Data collection and analysis (Part 1) (E1.1)
  • U4L14 Data collection and analysis (Part 2) (E1.1)
  • U4L15 Report writing (E2.1)
  • U4L16 Design a plan (E1.2)
  • U4L17 Gather and organize data (E1.3)
  • U4L18 Present a summary of the culminating investigation (E2.2)
  • U4L19 Analyze, interpret, summarize data and draw conclusion (E1.4 E1.5)
  • U4L20 Respond to critiques (E2.3)
  • U4L21 Critique the mathematical work of others (E2.4)
  • U4L22 Review
  • U4L23 Review
  • U4L24 Review
  • Finish and hand in MDM4U Unit4 Assignment at the end of lesson
  • MDM4U Unit4 Online Test
  • MDM4U Final Project
  • MDM4U Final Exam
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