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. TOC: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
