Students delve into probability distributions, exploring different types such as binomial and normal distributions. They calculate the expected values of these distributions, understanding how they predict average outcomes in repeated experiments or trials. This section enhances their ability to analyze and interpret data, preparing them for advanced studies in statistics and roles in fields where decision-making is based on statistical predictions, like finance and risk management.

This segment covers the core principles of probability theory, including the laws of probability, the concept of independent and dependent events, and the use of probability trees and Venn diagrams. Through these exercises, students gain a thorough understanding of how probability models the randomness and uncertainty of processes in the natural and social sciences, providing a foundation for further academic pursuits in mathematics and science.

Students explore compound and conditional probabilities, learning to calculate the likelihood of combined events and the probability of an event given the occurrence of another. These concepts are critical for solving complex problems in areas such as genetics, marketing analysis, and epidemiology. This practice not only sharpens their analytical skills but also deepens their understanding of interdependencies in statistical events.