Vol. 4, Issue 2, Part A (2022)

Probability theory provides a practical framework for reasoning under uncertainty. It helps describe how likely events are, how outcomes vary, and how decisions can be improved when information is incomplete. This paper outlines the basic ideas of probability, traces its early development, and explains core concepts such as sample spaces, events, and probability laws. It then introduces random variables and common distributions, including binomial and normal models. These ideas support key risk analysis tools like expected value, variance, and decision trees. The paper closes with real examples from finance, insurance, and medicine that show how probability theory guides sound decision making.