Random processes, also known as stochastic processes, refer to systems or phenomena that evolve over time in a probabilistic manner. These processes exhibit randomness, uncertainty, and unpredictability in their behavior. Random processes are commonly used in various fields such as statistics, physics, biology, engineering, and economics to model and analyze complex systems where outcomes are not deterministic. Random processes can be classified into different types based on their characteristics and properties, such as discrete-time or continuous-time processes, stationary or non-stationary processes, and ergodic or non-ergodic processes. Statistical tools and techniques are often used to analyze and study random processes, such as probability theory, stochastic calculus, and time series analysis. Overall, random processes provide a framework for understanding and modeling the inherent randomness and variability in natural and man-made systems, making them a crucial area of research in many scientific disciplines.