Bayes' Theorem (Introduction)
Mathematics · JC 2 · Probability and Discrete Distributions · Semester 2

Bayes' Theorem (Introduction)

Students will apply Bayes' Theorem to update probabilities based on new evidence.

MOE Syllabus OutcomesSingapore MOE H2 Mathematics (9758): Probability and Statistics: 1.1 ProbabilitySingapore MOE H2 Mathematics (9758): Probability and Statistics: Addition and multiplication principles for countingSingapore MOE H2 Mathematics (9758): Probability and Statistics: Use of permutation and combination

About This Topic

Students will apply Bayes' Theorem to update probabilities based on new evidence.

Key Questions

  1. Explain the utility of Bayes' Theorem in real-world scenarios.
  2. Analyze how prior probabilities are updated with new information using Bayes' Theorem.
  3. Construct a conditional probability using Bayes' Theorem.

Active Learning Ideas

See all activities→

Activities & Teaching Strategies

See all activities

Planning templates for Mathematics

Lesson Plan

5E Model

The 5E Model structures lessons through five phases (Engage, Explore, Explain, Elaborate, and Evaluate), guiding students from curiosity to deep understanding through inquiry-based learning.

Unit Planner

Math Unit

Plan a multi-week math unit with conceptual coherence: from building number sense and procedural fluency to applying skills in context and developing mathematical reasoning across a connected sequence of lessons.

Rubric

Math Rubric

Build a math rubric that assesses problem-solving, mathematical reasoning, and communication alongside procedural accuracy, giving students feedback on how they think, not just whether they got the right answer.

More in Probability and Discrete Distributions

Basic Probability Concepts

Reviewing fundamental probability definitions, events, and sample spaces.

8 methodologies

Permutations and Combinations

Using permutations and combinations to solve complex counting problems.

8 methodologies

Conditional Probability and Independence

Understanding conditional probability and the concept of independent events.

8 methodologies

Discrete Random Variables and Probability Distributions

Defining discrete random variables and their probability distributions.

8 methodologies

Expectation and Variance of Discrete Random Variables

Calculating the expected value and variance for discrete random variables.

8 methodologies

Binomial Distribution

Modeling scenarios with a fixed number of independent trials and two possible outcomes.

8 methodologies

Edited by Adriana Perusin, Editor-in-Chief, Flip Education
Synthesized by Flip Education from Lyman's Think-Pair-Share collaborative-discussion routine (1981)