Products related to Probability:
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Probability Essentials
We have made small changes throughout the book, including the exercises, and we have tried to correct if not all, then at least most of the typos.We wish to thank the many colleagues and students who have commented c- structively on the book since its publication two years ago, and in particular Professors Valentin Petrov, Esko Valkeila, Volker Priebe, and Frank Knight.Jean Jacod, Paris Philip Protter, Ithaca March, 2002 Preface to the Second Printing of the Second Edition We have bene?ted greatly from the long list of typos and small suggestions sent to us by Professor Luis Tenorio.These corrections have improved the book in subtle yet important ways, and the authors are most grateful to him.Jean Jacod, Paris Philip Protter, Ithaca January, 2004 Preface to the First Edition We present here a one semester course on Probability Theory.We also treat measure theory and Lebesgue integration, concentrating on those aspects which are especially germane to the study of Probability Theory.The book is intended to ?ll a current need: there are mathematically sophisticated s- dents and researchers (especially in Engineering, Economics, and Statistics) who need a proper grounding in Probability in order to pursue their primary interests.Many Probability texts available today are celebrations of Pr- ability Theory, containing treatments of fascinating topics to be sure, but nevertheless they make it di?cult to construct a lean one semester course that covers (what we believe) are the essential topics.
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Understanding Probability
Understanding Probability is a unique and stimulating approach to a first course in probability.The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for probabilities.The second part, covering a wide range of topics, teaches clearly and simply the basics of probability.This fully revised third edition has been packed with even more exercises and examples and it includes new sections on Bayesian inference, Markov chain Monte-Carlo simulation, hitting probabilities in random walks and Brownian motion, and a new chapter on continuous-time Markov chains with applications.Here you will find all the material taught in an introductory probability course.The first part of the book, with its easy-going style, can be read by anybody with a reasonable background in high school mathematics.The second part of the book requires a basic course in calculus.
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Teaching Probability
Written by leading subject specialists, Teaching Probability is designed to support teaching concepts in probability by providing a new approach to this difficult subject from a perspective not limited by a syllabus, giving teachers both theoretical and practical knowledge of an innovative way of teaching probability.This alternative approach to teaching probability focuses on the methods that teachers can apply to help their students engage with the topic using experiments and mathematical models to solve problems, considering how to overcome common misconceptions and the way in which probability can be communicated.
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Probability : An Introduction
Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour.This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields.It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains. A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures.The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford.The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit theorem.There is an account of moment generating functions and their applications.The following three chapters are about branching processes, random walks, and continuous-time random processes such as the Poisson process.The final chapter is a fairly extensive account of Markov chains in discrete time. This second edition develops the success of the first edition through an updated presentation, the extensive new chapter on Markov chains, and a number of new sections to ensure comprehensive coverage of the syllabi at major universities.
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What is the probability with a coin in probability in math?
In probability theory, the probability of an event occurring when flipping a fair coin is 0.5. This means that there is an equal chance of the coin landing on either heads or tails. The probability is calculated by dividing the number of favorable outcomes (in this case, landing on either heads or tails) by the total number of possible outcomes (which is 2 for a coin flip). Therefore, the probability of getting heads or tails when flipping a fair coin is 0.5 or 50%.
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What is the probability of a coin in probability in math?
In probability theory, the probability of a coin landing on either heads or tails is 0.5 or 50%. This is because there are only two possible outcomes when flipping a fair coin, and each outcome is equally likely. Therefore, the probability of the coin landing on heads is 0.5 and the probability of it landing on tails is also 0.5.
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What is the conditional probability in probability theory when flipping a coin?
In probability theory, the conditional probability when flipping a coin refers to the probability of a certain event occurring given that another event has already occurred. For example, if we flip a fair coin and want to find the probability of getting a head given that the coin landed on heads, this would be an example of conditional probability. Mathematically, conditional probability is calculated by dividing the probability of the intersection of the two events by the probability of the given event.
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What is the probability of flipping a coin?
The probability of flipping a fair coin and getting either heads or tails is 1/2 or 50%. This is because there are only two possible outcomes - heads or tails - and each outcome is equally likely to occur. Therefore, the probability of getting heads or tails on a single coin flip is 1/2.
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Probability via Expectation
The third edition of 1992 constituted a major reworking of the original text, and the preface to that edition still represents my position on the issues that stimulated me first to write.The present edition contains a number of minor modifications and corrections, but its principal innovation is the addition of material on dynamic programming, optimal allocation, option pricing and large deviations.These are substantial topics, but ones into which one can gain an insight with less labour than is generally thought.They all involve the expectation concept in an essential fashion, even the treatment of option pricing, which seems initially to forswear expectation in favour of an arbitrage criterion.I am grateful to readers and to Springer-Verlag for their continuing interest in the approach taken in this work.Peter Whittle Preface to the Third Edition This book is a complete revision of the earlier work Probability which appeared in 1970.While revised so radically and incorporatingso much new material as to amount to a new text, it preserves both the aim and the approach of the original.That aim was stated as the provision of a 'first text in probability, demanding a reasonable but not extensive knowledge of mathematics, and taking the reader to what one might describe as a good intermediate level' .In doing so it attempted to break away from stereotyped applications, and consider applications of a more novel and significant character.
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Probability with Martingales
Probability theory is nowadays applied in a huge variety of fields including physics, engineering, biology, economics and the social sciences.This book is a modern, lively and rigorous account which has Doob's theory of martingales in discrete time as its main theme.It proves important results such as Kolmogorov's Strong Law of Large Numbers and the Three-Series Theorem by martingale techniques, and the Central Limit Theorem via the use of characteristic functions.A distinguishing feature is its determination to keep the probability flowing at a nice tempo.It achieves this by being selective rather than encyclopaedic, presenting only what is essential to understand the fundamentals; and it assumes certain key results from measure theory in the main text.These measure-theoretic results are proved in full in appendices, so that the book is completely self-contained.The book is written for students, not for researchers, and has evolved through several years of class testing.Exercises play a vital rôle. Interesting and challenging problems, some with hints, consolidate what has already been learnt, and provide motivation to discover more of the subject than can be covered in a single introduction.
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Probability For Dummies
Learn how to calculate your chances with easy-to-understand explanations of probability Probability—the likelihood or chance of an event occurring—is an important branch of mathematics used in business and economics, finance, engineering, physics, and beyond.We see probability at work every day in areas such as weather forecasting, investing, and sports betting.Packed with real-life examples and mathematical problems with thorough explanations, Probability For Dummies helps students, professionals, and the everyday reader learn the basics.Topics include set theory, counting, permutations and combinations, random variables, conditional probability, joint distributions, conditional expectations, and probability modeling.Pass your probability class and play your cards right, with this accessible Dummies guide.Understand how probability impacts daily lifeDiscover what counting rules are and how to use themPractice probability concepts with sample problems and explanationsGet clear explanations of all the topics in your probability or statistics class Probability For Dummies is the perfect Dummies guide for college students, amateur and professional gamblers, investors, insurance professionals, and anyone preparing for the actuarial exam.
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High-Probability Trading
"The Goal Is to Teach All Traders to Think with the Mindset of a Successful Trader..." While successful trading requires tremendous skill and knowledge, it begins and ends with mindset.What do exceptional traders think when they purchase a quality stock and the price immediately plummets?How do they keep one bad trade from destroying their confidence - and bankroll?What do they know that the rest of us don't? "Some trades are not worth the risk and should never be done."High Probability Trading" shows you how to trade only when the odds are in your favor.From descriptions of the software and equipment an exceptional trader needs high probability signals that either a top or bottom has been reached, it is today's most complete guidebook to thinking like an exceptional trader - every day, on every trade. "It's not how good you are at one individual thing, but it's the culmination of every aspect of trading that makes one successful."Before he became a successful trader, Marcel Link spent years wading from one system to the next, using trial and error to figure out what worked, what didn't, and why. In "High Probability Trading", Link reveals the steps he took to become a consistent, patient, and winning trader - by learning what to watch for, what to watch out for, and what to do to make each trade a high probability trade. "Why do a select few traders repeatedly make money while the masses lose?What do bad traders do that good traders avoid, and what do winning traders do that is different?Throughout this book I will detail how successful traders behave differently and consistently make money by making high probability trades and avoiding common pitfalls..." - From the preface.Within 6 months of beginning their careers full of promise and hope, most traders are literally out of money and out of trading. "High Probability Trading" reduces the likelihood that you will have to pay this "traders' tuition," by detailing a market-proven program for weathering those first few months and becoming a profitable trader from the beginning.Combining a uniquely blunt look at the realities of trading with examples, charts, and case studies detailing actual hits and misses of both short- and long-term traders, this straightforward guidebook discusses: the 10 consistent attributes of a successful trader, and how to make them work for you; strategies for controlling emotions in the heat of trading battle; technical analysis methods for identifying trends, breakouts, reversals, and more; market-tested signals for consistently improving the timing of entry and exit points; how to "trade the news" - and understand when the market has already discounted it; and learning how to get out of a bad trade before it can hurt you. The best traders enter the markets only when the odds are in their favor. "High Probability Trading" shows you how to know the difference between low and high probability situations, and only trade the latter.It goes far beyond simply pointing out the weaknesses and blind spots that hinder most traders to explaining how those defects can be understood, overcome, and turned to each trader's advantage.While it is a cliche, it is also true that there are no bad traders, only bad trades.Let "High Probability Trading" show you how to weed the bad trades from your trading day by helping you see them before they occur.Packed with charts, trading tips, and questions traders should be asking themselves, plus real examples of traders in every market situation, this powerful book will first give you the knowledge and tools you need to tame the markets and then show you how to meld them seamlessly into a customized trading program - one that will help you join the ranks of elite traders and increase your probability of success on every trade.
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What is the probability of a coin toss?
The probability of a coin toss resulting in either heads or tails is 50%. This is because there are only two possible outcomes - heads or tails - and they are equally likely to occur. Therefore, the probability of getting either heads or tails is 1/2, or 50%.
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How do you calculate the probability with a coin?
To calculate the probability with a coin, you need to determine the total number of possible outcomes and the number of favorable outcomes. Since a coin has two sides (heads and tails), there are two possible outcomes. The probability of getting heads or tails on a fair coin is 1/2 or 0.5. This is because there is one favorable outcome (either heads or tails) out of the two possible outcomes.
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What is the highest probability when tossing a coin?
When tossing a fair coin, the highest probability is that it will land on either heads or tails, each with a probability of 0.5 or 50%. This is because there are only two possible outcomes when tossing a coin - heads or tails - and they are equally likely to occur. Therefore, the highest probability when tossing a coin is 50%.
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How often is the probability when flipping a coin?
The probability of flipping a coin is 50% or 1/2 for each outcome, which means that it is equally likely to land on heads or tails. This probability remains the same for each individual flip, regardless of the outcome of previous flips. Therefore, the probability of flipping a coin is consistent and does not change over time.
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