This is a course on the fundamentals of probability geared towards first- or second-year graduate students who are interested in a rigorous development of the subject. The course covers most of the topics in 6.431 (sample space, random variables, expectations, transforms, Bernoulli and Poisson processes, finite Markov chains, limit theorems) but at a faster pace and in more depth. There are also a number of additional topics, such as language, terminology, and key results from measure theory; interchange of limits and expectations; multivariate Gaussian distributions; deeper understanding of conditional distributions and expectations
This is an introductory probability textbook, published by the American Mathematical Society. It is ...
Goals: An introduction to the basic topics of mathematical probability theory, in preparation for a ...
Probability is an area of mathematics of tremendous contemporary importance across all aspects of hu...
In this course, the student will learn the basic terminology and concepts of probability theory, inc...
This is a pre-requisite for almost all graduate level courses in communications, signal processing, ...
Suitable for a graduate course in analytic probability, this text requires only a limited background...
This course introduces students to probability and random variable. Topics include distribution func...
This is a pre-requisite for almost all graduate level courses in communications, signal processing, ...
This course introduces students to probability and random variables. Topics include distribution fun...
This textbook explores probability and stochastic processes at a level that does not require any pri...
This second edition of the popular textbook contains a comprehensive course in modern probability th...
This course provides an elementary introduction to probability and statistics with applications. Top...
Frequency distributions. Summary statistics. Bivariate frequency distributions. Conditional sample m...
This volume presents topics in probability theory covered during a first-year graduate course given ...
The goal of this course is to introduce students to the basic probability theory and mathematical st...
This is an introductory probability textbook, published by the American Mathematical Society. It is ...
Goals: An introduction to the basic topics of mathematical probability theory, in preparation for a ...
Probability is an area of mathematics of tremendous contemporary importance across all aspects of hu...
In this course, the student will learn the basic terminology and concepts of probability theory, inc...
This is a pre-requisite for almost all graduate level courses in communications, signal processing, ...
Suitable for a graduate course in analytic probability, this text requires only a limited background...
This course introduces students to probability and random variable. Topics include distribution func...
This is a pre-requisite for almost all graduate level courses in communications, signal processing, ...
This course introduces students to probability and random variables. Topics include distribution fun...
This textbook explores probability and stochastic processes at a level that does not require any pri...
This second edition of the popular textbook contains a comprehensive course in modern probability th...
This course provides an elementary introduction to probability and statistics with applications. Top...
Frequency distributions. Summary statistics. Bivariate frequency distributions. Conditional sample m...
This volume presents topics in probability theory covered during a first-year graduate course given ...
The goal of this course is to introduce students to the basic probability theory and mathematical st...
This is an introductory probability textbook, published by the American Mathematical Society. It is ...
Goals: An introduction to the basic topics of mathematical probability theory, in preparation for a ...
Probability is an area of mathematics of tremendous contemporary importance across all aspects of hu...