ESMA 6600 Probability Theory (I)

General	Syllabus
	List of Stories of the Data sets
	Homeworks and Exams
R	An Introduction to R
	R Programing Language and User-Written Functions
	Some R Commands
Probability	Introduction
	Conditional Probability and Independence
	Combinatorics
	Random Variables and Random Vectors
	Expectation
	Functions of a R.V. - Transformations
	Inequalities
	Limit Theorems
	Approximations
Some Standard Distributions	Discrete Distributions
	Continuous Distributions
Stochastic Processes	Markov Chains
	Continuous-time Markov Chains
	Poisson Process
	Martingales
	Brownian Motion and Stationary Processes
Generating Random Variables	General Methods
	Special Cases
	MCMC - Markov Chain Monte Carlo