Data Management – Grade 12 (University Preparation Level)

The Grade 12 university preparation course Mathematics of Data Management is designed to satisfy the prerequisites for a number of university programs that may include statistics courses, such as those found in the social sciences and the humanities. The expectations in the strands of this course require students to apply mathematical process skills developed in prerequisite courses, such as problem solving, reasoning, and communication, to the study of probability and statistics. The Counting and Probability strand extends the basic probability concepts learned in the elementary school program and introduces counting techniques such as the use of permutations and combinations; these techniques are applied to both counting and probability problems. The Probability Distributions strand introduces the concept of probability distributions; these include the normal distribution, which is important in the study of statistics. In the Organization of Data for Analysis strand, students examine, use, and develop methods for organizing large amounts of data, while in the Statistical Analysis strand, students investigate and develop an understanding of powerful concepts used to analyse and interpret large amounts of data. These concepts are developed with the use of technological tools such as spreadsheets and Fathom, a ministry-licensed dynamic statistical program. The Culminating Data Management Investigation strand requires students to undertake a culminating investigation dealing with a significant issue that will require the application of the skills from the other strands of the course.

Course Outline

  • Chapter 1: Matrices
  • Chapter 2: Permutations and Combinations
  • Chapter 3: Pascal's Triangle and Binomial Theorem
  • Chapter 4: Statistics of One Variable
  • Chapter 5: Statistics of Two Variables
  • Chapter 6: Introduction to Probability
  • Chapter 7: Probability Distributions
  • Chapter 8: The Normal Distribution
  • Chapter 9: Project Preparations (Optional)

Course Calendar

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