Set theory forms the foundation of probability, dealing with collections of events and their relationships. Key operations like union, intersection, and complement help in analyzing event outcomes. The rules of probability define how likely events are to occur. The addition rule calculates the probability of either of two events occurring, the multiplication rule determines the probability of both events happening together, and the complement rule finds the probability of an event not occurring. These concepts are essential for understanding and solving probability-related problems. In this topic, a lecture notes and a teaching video are provided. Additionally, an students are compulsory to involve in an interactive activity, 1 quiz and 1 final assessment.

At the end of the topic, you will be able to:

1. To understand the basic concepts of set theory.
2. To understand the concepts of addition and multiplication rules in probability.
3. To solve the probability problem that relates to the addition and multiplication rules.

Counting rules, permutations, and combinations are key concepts in probability and combinatorics. Counting rules help determine the total number of possible outcomes for multiple events. Permutations refer to the arrangement of objects where the order matters, while combinations involve the selection of objects where the order does not matter. Permutations are used for tasks like arranging items, and combinations are used when selecting items without regard to their arrangement. These tools are essential for solving problems related to probability and decision-making. In this topic, a lecture notes and a teaching video are provided. Additionally, an students are compulsory to involve in an interactive activity, 1 quiz and 1 final assessment.

At the end of the topic, you will be able to:
1. To understand the concepts of counting rules, permutation and combination
2. To solve the problem involve counting rules, permutation and combination

Tree diagrams are a visual tool used to represent all possible outcomes of a series of events, helping to organize and calculate probabilities, especially in complex scenarios. They start from a single point, with branches representing the outcomes of each event. In addition, Bayes' Theorem is a key concept in probability theory that allows for updating the probability of a hypothesis based on new evidence. It relates the conditional probability of an event to the reverse conditional probability, making it useful in decision-making under uncertainty. Together, tree diagrams and Bayes' Theorem provide a structured approach to solving problems involving conditional probabilities. The construction of the tree diagram will be shown and solving conditional probability problem using Bayes’ theorem. Some examples are also given to give a better understanding on the topic. In this topic, a lecture notes and a teaching video are provided. Additionally, an students are compulsory to involve in an interactive activity, 1 quiz and 1 final assessment.

At the end of the topic, you will be able to:
1. To construct the tree diagram based on the information given.
2. To solve the conditional probability problem using Bayes' theorem.