PROBABILITIES

The probability concept. Classical and empirical definition of probability. Conditional probability and independence. Bayes law. Combinatorial analysis. The concept of random variables. One-dimensional distributions. Functions of random variables. Mean value, variance, correlation functions , correlation coefficient. Multi-dimensional distributions. Central limit theorem. Moment generating functions. Random walks. Stochastic processes. Master Equation, Langevin Equation, Fokker-Planck Equation, Markov Chains.

Objectives

Introduction to the concepts of discrete probability and combinations

Prerequisites

Non required

Syllabus

The probability concept. Classical and empirical definition of probability. Conditional probability and independence. Bayes law. Combinatorial analysis. The concept of random variables. One-dimensional distributions. Functions of random variables. Mean value, variance, correlation functions , correlation coefficient. Multi-dimensional distributions. Central limit theorem. Moment generating functions. Random walks. Stochastic processes. Master Equation, Langevin Equation, Fokker-Planck Equation, Markov Chains.