Data Management (MDM4U)

By the end of this course, students will:

• solve problems involving the probability of an event or a combination of events for discrete sample spaces;
• solve problems involving the application of permutations and combinations to determine the probability of an event.

By the end of this course, students will:

• demonstrate an understanding of discrete probability distributions, represent them numerically, graphically, and algebraically,determine expected values, and solve related problems from a variety of applications;
• demonstrate an understanding of continuous probability distributions, make connections to discrete probability distributions, determine standard deviations, describe key features of the normal distribution, and solve related problems from a variety of applications.

By the end of this course, students will:

• demonstrate an understanding of the role of data in statistical studies and the variability inherent in data, and distinguish different types of data;
• describe the characteristics of a good sample, some sampling techniques, and principles of primary data collection, and collect and organize data to solve a problem.

By the end of this course, students will:

• analyse, interpret, and draw conclusions from one-variable data
  using numerical and graphical summaries;
• analyse, interpret, and draw conclusions from two-variable data
  using numerical, graphical, and algebraic summaries;
• demonstrate an understanding of the applications of data management used by the media and the advertising industry and in various occupations.

By the end of this course, students will:

• design and carry out a culminating investigation* that requires the integration and application of the knowledge and skills related to the expectations of this course;
• communicate the findings of a culminating investigation and provide constructive critiques of the investigations of others.