Many probability books are written by mathematicians and have the built in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance, and engineering.
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"This book is a rather comfortable probability path leading from fundamental notions of measure theory and probability theory to martingale theory, since fundamental concepts and basic theorems are always illustrated by important examples and results of additional theoretical value." ―Statistics & Decision
"This textbook offers material for a one-semester course in probability, addressed to students whose primary focus is not necessarily mathematics...Each chapter is completed by an exercises section. Carefully selected examples enlighten the reader in many situations. The book is an excellent introduction to probability and its applications." ---Revue Roumaine de Mathématiques Pures et Appliquées
1. Sets and Events ; 2. Probability Spaces; 3. Random Variables, Elements and Measurable Maps; 4. Independence; 5. Integration and Expectation; 6. Convergence Concepts; 7. Laws of Large Numbers and Sums of Independent Random Variables; 8. Convergence in Distribution; 9. Characteristic Functions and the Central Limit Theorem; 10. Martingales; Index; References
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