Probability and stochastic processes
Probability theory and stochastic processes are foundational concepts in statistics that deal with uncertainty, randomness and the study of random phenomena.
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Probability theory provides the framework for quantifying and analyzing uncertainty. It provides a formal language to describe and reason about the likelihood of events or outcomes. Stochastic processes allow us to describe the evolution of random variables or events over time. Some common types of stochastic processes include Markov chains, Brownian motion, Poisson process, time series and Martingales. Probability theory and stochastic processes provide the statistical framework for reasoning about uncertainty and randomness. They enable the modelling, analysis and prediction of random phenomena in various fields, contributing to decision-making, risk assessment and understanding of complex systems.