An Introduction to Measure-Theoretic Probability, Second Edition, employs a classical approach to teaching students of statistics, mathematics, engineering, econometrics, finance, and other disciplines that measure theoretic probability. This book requires no prior knowledge of measure theory, discusses all its topics in great detail, and includes one chapter on the basics of ergodic theory and one chapter on two cases of statistical estimation. There is a considerable bend toward the way probability is actually used in statistical research, finance, and other academic and nonacademic applied pursuits. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced degree in statistics, probability and other related areas should be equipped with.

Key Features:-

  • Provides in a concise, yet detailed way, the bulk of probabilistic tools essential to a student work
  • Includes extensive exercises and practical examples to make complex ideas of advanced probability ac
  • All proofs presented in full detail and complete and detailed solutions to all exercises are availab
  • Considerable bend toward the way probability is used in statistics in non-mathematical settings in a

More Details about An Introduction to Measuretheoretic Probability

General Information  
Author(s)George G Roussas
PublisherElsevier Science
Publish YearJanuary 2014