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Author: Edmund F. Byrne Publisher: Springer ISBN: Category : Mathematics Languages : en Pages : 376
Book Description
Modern physics has accustomed us to consider events which cannot give rise to certainty in our knowledge. A scientific knowledge of such events is nevertheless possible. The method which has enabled us to obtain a stable and exact knowledge about uncertain events consists in a kind of changing of plane and in the replacing of the study of indi vidual phenomena by the study of statistical aggregates to which those phenomena can give rise. A statistical aggregate is not a collection of real phenomena, among which some would happen more often, others more rarely. It is a set of possibilities relative to a certain object or to a certain type of phenomenon. For example, we could consider the differ ent ways in which a die, thrown in given conditions, can fall: they are the possible results of a certain trial, the casting of the die (in the fore seen conditions). The set of those results constitutes effectively a set of possibilities, relative to a phenomenon of a certain type, the fall of the die in specified circumstances. Similarly, it is possible to consider the different velocities which can affect a molecule in a volume of gas; the set of those velocities constitutes effectively a set of possible values which a physical property, namely the velocity of a molecule, can have.
Author: Edmund F. Byrne Publisher: Springer ISBN: Category : Mathematics Languages : en Pages : 376
Book Description
Modern physics has accustomed us to consider events which cannot give rise to certainty in our knowledge. A scientific knowledge of such events is nevertheless possible. The method which has enabled us to obtain a stable and exact knowledge about uncertain events consists in a kind of changing of plane and in the replacing of the study of indi vidual phenomena by the study of statistical aggregates to which those phenomena can give rise. A statistical aggregate is not a collection of real phenomena, among which some would happen more often, others more rarely. It is a set of possibilities relative to a certain object or to a certain type of phenomenon. For example, we could consider the differ ent ways in which a die, thrown in given conditions, can fall: they are the possible results of a certain trial, the casting of the die (in the fore seen conditions). The set of those results constitutes effectively a set of possibilities, relative to a phenomenon of a certain type, the fall of the die in specified circumstances. Similarly, it is possible to consider the different velocities which can affect a molecule in a volume of gas; the set of those velocities constitutes effectively a set of possible values which a physical property, namely the velocity of a molecule, can have.
Author: Jim Albert Publisher: CRC Press ISBN: 1351030132 Category : Mathematics Languages : en Pages : 553
Book Description
Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.
Author: Daniel W. Stroock Publisher: Cambridge University Press ISBN: 1139494619 Category : Mathematics Languages : en Pages : 550
Book Description
This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to probability theory and the analytic ideas and tools on which the modern theory relies. It includes more than 750 exercises. Much of the content has undergone significant revision. In particular, the treatment of Levy processes has been rewritten, and a detailed account of Gaussian measures on a Banach space is given.
Author: Jim Pitman Publisher: Springer Science & Business Media ISBN: 1461243742 Category : Mathematics Languages : en Pages : 564
Book Description
This is a text for a one-quarter or one-semester course in probability, aimed at students who have done a year of calculus. The book is organised so a student can learn the fundamental ideas of probability from the first three chapters without reliance on calculus. Later chapters develop these ideas further using calculus tools. The book contains more than the usual number of examples worked out in detail. The most valuable thing for students to learn from a course like this is how to pick up a probability problem in a new setting and relate it to the standard body of theory. The more they see this happen in class, and the more they do it themselves in exercises, the better. The style of the text is deliberately informal. My experience is that students learn more from intuitive explanations, diagrams, and examples than they do from theorems and proofs. So the emphasis is on problem solving rather than theory.
Author: Ian Hacking Publisher: Cambridge University Press ISBN: 9780521685573 Category : History Languages : en Pages : 260
Book Description
Historical records show that there was no real concept of probability in Europe before the mid-seventeenth century, although the use of dice and other randomizing objects was commonplace. First published in 1975, this edition includes an introduction that contextualizes his book in light of developing philosophical trends.
Author: J. Hoffman-Jorgensen Publisher: CRC Press ISBN: 9780412052217 Category : Mathematics Languages : en Pages : 636
Book Description
Volume I of this two-volume text and reference work begins by providing a foundation in measure and integration theory. It then offers a systematic introduction to probability theory, and in particular, those parts that are used in statistics. This volume discusses the law of large numbers for independent and non-independent random variables, transforms, special distributions, convergence in law, the central limit theorem for normal and infinitely divisible laws, conditional expectations and martingales. Unusual topics include the uniqueness and convergence theorem for general transforms with characteristic functions, Laplace transforms, moment transforms and generating functions as special examples. The text contains substantive applications, e.g., epidemic models, the ballot problem, stock market models and water reservoir models, and discussion of the historical background. The exercise sets contain a variety of problems ranging from simple exercises to extensions of the theory.
Author: Michael Kaplan Publisher: Penguin ISBN: 1440684510 Category : Mathematics Languages : en Pages : 337
Book Description
A compelling journey through history, mathematics, and philosophy, charting humanity’s struggle against randomness Our lives are played out in the arena of chance. However little we recognize it in our day-to-day existence, we are always riding the odds, seeking out certainty but settling—reluctantly—for likelihood, building our beliefs on the shadowy props of probability. Chances Are is the story of man’s millennia-long search for the tools to manage the recurrent but unpredictable—to help us prevent, or at least mitigate, the seemingly random blows of disaster, disease, and injustice. In these pages, we meet the brilliant individuals who developed the first abstract formulations of probability, as well as the intrepid visionaries who recognized their practical applications—from gamblers to military strategists to meteorologists to medical researchers, from blackjack to our own mortality.
Author: J. Hoffman-Jorgensen Publisher: Routledge ISBN: 1351421581 Category : Mathematics Languages : en Pages : 630
Book Description
Volume I of this two-volume text and reference work begins by providing a foundation in measure and integration theory. It then offers a systematic introduction to probability theory, and in particular, those parts that are used in statistics. This volume discusses the law of large numbers for independent and non-independent random variables, transforms, special distributions, convergence in law, the central limit theorem for normal and infinitely divisible laws, conditional expectations and martingales. Unusual topics include the uniqueness and convergence theorem for general transforms with characteristic functions, Laplace transforms, moment transforms and generating functions as special examples. The text contains substantive applications, e.g., epidemic models, the ballot problem, stock market models and water reservoir models, and discussion of the historical background. The exercise sets contain a variety of problems ranging from simple exercises to extensions of the theory.
Author: Edmund F. Byrne
Author: Edmund F. Byrne
Author: Jim Albert
Author: Daniel W. Stroock
Author: Edmund F. Byrne
Author: Jim Pitman
Author: Ian Hacking
Author: J. Hoffman-Jorgensen
Author: Michael Kaplan
Author: 
Author: J. Hoffman-Jorgensen