𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

A Natural Introduction to Probability Theory

✍ Scribed by R. Meester


Publisher
BirkhΓ€user Basel
Year
2008
Tongue
English
Leaves
201
Edition
2nd
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


"The book [is] an excellent new introductory text on probability. The classical way of teaching probability is based on measure theory. In this book discrete and continuous probability are studied with mathematical precision, within the realm of Riemann integration and not using notions from measure theory…. Numerous topics are discussed, such as: random walks, weak laws of large numbers, infinitely many repetitions, strong laws of large numbers, branching processes, weak convergence and [the] central limit theorem. The theory is illustrated with many original and surprising examples and problems." Zentralblatt Math

"Most textbooks designed for a one-year course in mathematical statistics cover probability in the first few chapters as preparation for the statistics to come. This book in some ways resembles the first part of such textbooks: it's all probability, no statistics. But it does the probability more fully than usual, spending lots of time on motivation, explanation, and rigorous development of the mathematics…. The exposition is usually clear and eloquent…. Overall, this is a five-star book on probability that could be used as a textbook or as a supplement." MAA online


πŸ“œ SIMILAR VOLUMES


A Natural Introduction to Probability Th
✍ Ronald Meester πŸ“‚ Library πŸ“… 2008 🌐 English

Compactly written, but nevertheless very readable, appealing to intuition, this introduction to probability theory is an excellent textbook for a one-semester course for undergraduates in any direction that uses probabilistic ideas. Technical machinery is only introduced when necessary. The route is

Introduction to Probability Theory
✍ Feller W. πŸ“‚ Library πŸ“… 1967 πŸ› Wiley 🌐 English

Major changes in this edition include the substitution of probabilistic arguments for combinatorial artifices, and the addition of new sections on branching processes, Markov chains, and the De Moivre-Laplace theorem.