Introduction to Probability

An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields This is the currently used textbook for Probabilistic Systems Analysis, an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students The book covers the fundamentals of probability theory probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems , which are typically part of a first course on the subject It also contains, a number of advanced topics, from which an instructor can choose to match the goals of a particular course These topics include transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning Some of the mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail at the level of advanced calculus in the numerous solved theoretical problems The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad. Read Introduction to Probability Author Dimitri P. Bertsekas – kino-fada.fr Well done textbook introducing all the main topics in probability, as well as Markov Chains, Bayesian Statistical Inference, and Classical Statistical Inference I would also recommend the free MIT course at edX, Introd...This is an excelent introduction to calculus based probability It is easily accessible to people coming from any dicipline.I read it as part of my graduate studies at GMU ECE 528.

• English
• 06 April 2018
Dimitri P. Bertsekas
• Hardcover
• 430 pages
• 188652940X
• Dimitri P. Bertsekas
• Introduction to Probability