Understand events as subsets of a sample space using features of the outcomes or their mathematical relationships (unions, intersections, or complements). Recognize that events are independent if the chance of them happening together equals the product of their individual probabilities. The conditional probability of one event given another is calculated as the probability of both divided by the probability of the second, with independence implying the conditional probability of one given the second is constant.

Use two-way frequency tables to examine data with two associated categories. Utilize this table to examine event independence and estimate conditional probabilities. This can be applied to real life scenarios, such as estimating a student's favourite subject based on their grade. Also, understand conditional probability and independence through everyday examples.

Use the fraction of the second event’s outcomes that belong to the first to find the conditional probability of the first given the second. Apply essential rules, such as the Addition Rule for calculating the probability of either event occurring. Implement the general Multiplication Rule in a consistent probability model for computing the likelihood of both events happening. Utilize permutations and combinations to find probabilities of complex events and resolve issues.