Artificial Intelligence Programming Practice Exam 2025 - Free AI Programming Practice Questions and Study Guide

Stochastic Calculus is fundamentally different from regular calculus due to its emphasis on random variables and processes. While regular calculus typically deals with deterministic functions and equations that produce predictable outcomes, stochastic calculus is designed to handle situations where randomness and uncertainty are key components.

In this realm, random variables are essential since they account for the inherent unpredictability in many systems, particularly in fields like finance, physics, and engineering where processes are subject to randomness. Stochastic calculus allows practitioners to perform analysis on functions that evolve over time with stochastic elements, enabling the modeling of complex systems where outcomes can vary due to random influences.

This approach also leads to specific mathematical tools and frameworks, such as Itô's lemma and stochastic differentials, which do not have counterparts in traditional calculus. Through this lens, it becomes clear that the emphasis on random variables is what primarily distinguishes stochastic calculus from its deterministic counterpart.