This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail.
Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory.Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible.
This textbook is an introduction to rigorous probability theory using measure theory. It provides rigorous, complete proofs of all the essential introductory mathematical results of probability theory and measure theory. More advanced or specialized areas are entirely omitted or only hinted at. For example, the text includes a complete proof of the classical central limit theorem, including the necessary continuity theorem for characteristic functions, but the more general Lindeberg central limit theorem is only outlined and is not proved. Similarly, all necessary facts from measure theory are proved before they are used, but more abstract or advanced measure theory results are not included. Furthermore, measure theory is discussed as much as possible purely in terms of probability, as opposed to being treated as a separate subject which must be mastered before probability theory can be understood.
Jeffrey S. Rosenthal, author of the bestseller Struck by Lightning: The Curious World of Probabilities, was born on Friday the thirteenth, a fact that he discovered long after he had become one of the world’s pre-eminent statisticians. Had he been living ignorantly and innocently under an unlucky cloud for all those years? Or is thirteen just another number? As a scientist and a man of reason, Rosenthal has long considered the value of luck, good and bad, seeking to measure chance and hope in formulas scratched out on chalkboards. In Knock on Wood, with great humour and irreverence, Rosenthal divines the world of luck, fate and chance, putting his considerable scientific acumen to the test in deducing whether luck is real or the mere stuff of superstition.
Features an introduction to probability theory using measure theory. This work provides proofs of the essential introductory results and presents the measure theory and mathematical details in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects.
From terrorist attacks to big money jackpots, Struck by Lightning deconstructs the odds and oddities of chance, examining both the relevant and irreverent role of randomness in our everyday lives. Human beings have long been both fascinated and appalled by randomness. On the one hand, we love the thrill of a surprise party, the unpredictability of a budding romance, or the freedom of not knowing what tomorrow will bring. We are inexplicably delighted by strange coincidences and striking similarities. But we also hate uncertainty's dark side. From cancer to SARS, diseases strike with no apparent pattern. Terrorists attack, airplanes crash, bridges collapse, and we never know if we'll be that one in a million statistic. We are all constantly faced with situations and choices that involve randomness and uncertainty. A basic understanding of the rules of probability theory, applied to real-life circumstances, can help us to make sense of these situations, to avoid unnecessary fear, to seize the opportunities that randomness presents to us, and to actually enjoy the uncertainties we face. The reality is that when it comes to randomness, you can run, but you can't hide. So many aspects of our lives are governed by events that are simply not in our control. In this entertaining yet sophisticated look at the world of probabilities, author Jeffrey Rosenthal-an improbably talented math professor-explains the mechanics of randomness and teaches us how to develop an informed perspective on probability.
The undisputed leader on the subject of geriatrics—updated to reflect the most recent advances in the field A Doody's Core Title for 2023! The leading text on the subject of geriatrics, this comprehensive guide combines gerontology principles with clinical geriatrics, offering unmatched coverage of this area of medicine. Anchored in evidence-based medicine and patient-centered practice, Hazzard's Geriatric Medicine and Gerontology presents the most up-to-date, medical information available. This updated eighth edition reflects the continued growth and increasing sophistication of geriatrics as a defined medical discipline. The book focuses on the implementation of key concepts and covers the foundation for geriatrics, as well as frequently encountered syndromes found in older adults. In addition, it provides valuable insights into the simultaneous management of multiple conditions, including psychological and social issues and their interactions, an intrinsic aspect of geriatric patient care. Features: A greater emphasize on the growing knowledge base for key topics in the field, including gerontology, geriatrics, geriatric conditions, and palliative medicine NEW chapters on: Social Determinants of Health, Health Disparities and Health Equity Age Friendly Care Geriatrics Around the World The Patient Perspective Substance Use and Disorders Applied Clinical Geroscience Managing the Care of Patients with Multiple Chronic Conditions UPDATED contributions from a respected and diverse team of geriatricians and subspecialists to reflect clinical breakthroughs and advances NEW: Extensive coverage of the COVID-19 pandemic and its impact on vulnerable older adults Updated Learning Objectives and Key Clinical Points Hundreds of full-color images
THE WORLD'S #1 SURGERY TEXT--UPDATED TO INCLUDE STATE-OF-THE-ART EVIDENCE-BASED SURGICAL CARE AND LEADERSHIP GUIDANCE FOR TRAINEES AND PRACTICING SURGEONS The Tenth Edition of Schwartz's Principles of Surgery maintains the book's unmatched coverage of the foundations of surgery while bringing into sharper focus new and emerging technologies. We have entered a new era of surgery in which minimally invasive surgery, robotic surgery, and the use of computers and genomic information have improved the outcomes and quality of life for patients. With these advances in mind, all chapters have been updated with an emphasis on evidence-based, state-of-the-art surgical care. An exciting new chapter, "Fundamental Principles of Leadership Training in Surgery," expands the scope of the book beyond the operating room to encompass the actual development of surgeons. This edition is also enriched by an increased number of international chapter authors and a new chapter on Global Surgery. More than ever, Schwartz's Principles of Surgery is international in scope--a compendium of the knowledge and technique of the world's leading surgeons. Features More clinically relevant than ever, with emphasis on high-yield discussion of diagnosis and treatment of surgical disease, arranged by organ system and surgical specialty Content is supported by boxed key points, detailed anatomical figures, diagnostic and management algorithms, and key references Beautiful full-color design
From terrorist attacks to big money jackpots, Struck by Lightning deconstructs the odds and oddities of chance, examining both the relevant and irreverent role of randomness in our everyday lives. Human beings have long been both fascinated and appalled by randomness. On the one hand, we love the thrill of a surprise party, the unpredictability of a budding romance, or the freedom of not knowing what tomorrow will bring. We are inexplicably delighted by strange coincidences and striking similarities. But we also hate uncertainty's dark side. From cancer to SARS, diseases strike with no apparent pattern. Terrorists attack, airplanes crash, bridges collapse, and we never know if we'll be that one in a million statistic. We are all constantly faced with situations and choices that involve randomness and uncertainty. A basic understanding of the rules of probability theory, applied to real-life circumstances, can help us to make sense of these situations, to avoid unnecessary fear, to seize the opportunities that randomness presents to us, and to actually enjoy the uncertainties we face. The reality is that when it comes to randomness, you can run, but you can't hide. So many aspects of our lives are governed by events that are simply not in our control. In this entertaining yet sophisticated look at the world of probabilities, author Jeffrey Rosenthal-an improbably talented math professor-explains the mechanics of randomness and teaches us how to develop an informed perspective on probability.
Features an introduction to probability theory using measure theory. This work provides proofs of the essential introductory results and presents the measure theory and mathematical details in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects.
This textbook is an introduction to rigorous probability theory using measure theory. It provides rigorous, complete proofs of all the essential introductory mathematical results of probability theory and measure theory. More advanced or specialized areas are entirely omitted or only hinted at. For example, the text includes a complete proof of the classical central limit theorem, including the necessary continuity theorem for characteristic functions, but the more general Lindeberg central limit theorem is only outlined and is not proved. Similarly, all necessary facts from measure theory are proved before they are used, but more abstract or advanced measure theory results are not included. Furthermore, measure theory is discussed as much as possible purely in terms of probability, as opposed to being treated as a separate subject which must be mastered before probability theory can be understood.
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