M213:BayesianReasoningandProbabilityTheory

Bayesian Reasoning and Probability Theory

Does being tall make you more likely to become a professional athlete? If you flip a coin and get tails three times in a row, are you less likely to get tails again? Outcomes in a scenario may differ depending on what has already happened — and probability gives us the tools to reason carefully about that.

In M213 Bayesian Reasoning and Probability Theory, you will:


• Explore how past events can affect the chances of future outcomes, and learn what it means for events to be independent
• Apply Bayes' Rule and use tools like two-way tables and tree diagrams to calculate probabilities and determine whether events are connected
• Use technology to simulate random events, estimate probabilities, and interpret results

Examples of careers that use M213 concepts: biology, health research, and risk management.

Associated Badges

Learning Goals

Content & Practice Expectations

Each badge framework describes the mathematics skills and understandings that students will need to demonstrate to earn each badge through a set of Content & Practice Expectations (CPEs).

Assessments

Introduction to Badge Assessments

This document provides an overview of the different badging forms of assessment.

Portfolio Resources

A portfolio of evidence consists of student-produced artifacts that demonstrate proficiency against a badge’s CPEs. The portfolio development process involves students selecting and reflecting on artifacts that showcase their understanding of badge CPEs, followed by iterative teacher review and student-teacher conferencing until the work demonstrates proficiency.

Professional Learning Resources

Download a sample Professional Learning presentation for this badge that you may copy and customize to suit your needs. When available, samples of student work are provided for discussion.

Bayesian Reasoning and Probability Theory | XQ Learning