A Modern Introduction to Probability and Statistics

• Author : F.M. Dekking,C. Kraaikamp,H.P. Lopuhaä,L.E. Meester
• Publisher : Springer Science & Business Media
• Release : 30 March 2006

Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

• Author : Anirban DasGupta
• Publisher : Springer Science & Business Media
• Release : 17 May 2011

This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and

• Author : E. Rukmangadachari
• Publisher : Pearson Education India
• Release : 06 December 2021

This book is designed for engineering students studying the core paper on probability and statistics during their second or third years. It includes detailed explanation of theory with numerous examples and exercises, as well as relevant references to engineering applications. Each chapter also has numerous objective type questions and answers and hints are provided for all the exercise problems and objective type questions.

• Author : Milan Holický
• Publisher : Springer Science & Business Media
• Release : 04 August 2013

The theory of probability and mathematical statistics is becoming an indispensable discipline in many branches of science and engineering. This is caused by increasing significance of various uncertainties affecting performance of complex technological systems. Fundamental concepts and procedures used in analysis of these systems are often based on the theory of probability and mathematical statistics. The book sets out fundamental principles of the probability theory, supplemented by theoretical models of random variables, evaluation of experimental data, sampling theory, distribution updating

• Author : Leonard Asimow, Ph.D., ASA,Mark Maxwell, Ph.D., ASA
• Publisher : ACTEX Publications
• Release : 30 June 2015

This text is listed on the Course of Reading for SOA Exam P. Probability and Statistics with Applications is an introductory textbook designed to make the subject accessible to college freshmen and sophomores concurrent with Calc II and III, with a prerequisite of just one smester of calculus. It is organized specifically to meet the needs of students who are preparing for the Society of Actuaries qualifying Examination P and Casualty Actuarial Society's new Exam S. Sample actuarial exam problems

• Author : Nitis Mukhopadhyay
• Publisher : CRC Press
• Release : 22 March 2000

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, Probability and Statistical Inference studies the Helmert transformation for normal distributions and the waiting time between

• Author : Leon J. Gleser,Michael D. Perlman,S. James Press,Allan R. Sampson
• Publisher : Springer
• Release : 17 September 2011

Published in honor of the sixty-fifth birthday of Professor Ingram Olkin of Stanford University. Part I contains a brief biography of Professor Olkin and an interview with him discussing his career and his research interests. Part II contains 32 technical papers written in Professor Olkin's honor by his collaborators, colleagues, and Ph.D. students. These original papers cover a wealth of topics in mathematical and applied statistics, including probability inequalities and characterizations, multivariate analysis and association, linear and nonlinear models, ranking

• Author : William Mendenhall,Robert J. Beaver,Barbara M. Beaver
• Publisher : Cengage Learning
• Release : 01 January 2012

Used by hundreds of thousands of students since its first edition, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, continues to blend the best of its proven, error-free coverage with new innovations. Written for the higher end of the traditional introductory statistics market, the book takes advantage of modern technology--including computational software and interactive visual tools--to facilitate statistical reasoning as well as the interpretation of statistical results. In addition to showing how to apply statistical procedures, the authors explain how to

• Author : Ronald E. Walpole,Raymond H. Myers,Sharon L. Myers,Keying Ye
• Publisher : Unknown
• Release : 01 January 2016

This classic text provides a rigorous introduction to basic probability theory and statistical inference, illustrated by relevant applications. It assumes a background in calculus and offers a balance of theory and methodology.

• Author : James L. Johnson
• Publisher : John Wiley & Sons
• Release : 09 September 2011

Comprehensive and thorough development of both probability andstatistics for serious computer scientists; goal-oriented: "topresent the mathematical analysis underlying probabilityresults" Special emphases on simulation and discrete decision theory Mathematically-rich, but self-contained text, at a gentlepace Review of calculus and linear algebra in an appendix Mathematical interludes (in each chapter) which examinemathematical techniques in the context of probabilistic orstatistical importance Numerous section exercises, summaries, historical notes, andFurther Readings for reinforcement of content

• Author : Didier Dacunha-Castelle,Marie Duflo
• Publisher : Springer
• Release : 11 April 1986

How can we predict the future without asking an astrologer? When a phenomenon is not evolving, experiments can be repeated and observations therefore accumulated; this is what we have done in Volume I. However history does not repeat itself. Prediction of the future can only be based on the evolution observed in the past. Yet certain phenomena are stable enough so that observation in a sufficient interval of time gives usable information on the future or the mechanism of evolution.

• Author : Maria Dolores Ugarte,Ana F. Militino,Alan T. Arnholt
• Publisher : Chapman and Hall/CRC
• Release : 27 July 2015

Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Edition explores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs. New to the Second Edition Improvements to existing examples, problems, concepts, data, and functions New

• Author : Robert V. Hogg,Elliot A. Tanis
• Publisher : Macmillan College
• Release : 06 December 1988

This user-friendly introduction to the mathematics of probability and statistics (for readers with a background in calculus) uses numerous applications--drawn from biology, education, economics, engineering, environmental studies, exercise science, health science, manufacturing, opinion polls, psychology, sociology, and sports--to help explain and motivate the concepts. A review of selected mathematical techniques is included, and an accompanying CD-ROM contains many of the figures (many animated), and the data included in the examples and exercises (stored in both Minitab compatible format and ASCII).

• Author : Svetlozar T. Rachev,Markus Hoechstoetter,Frank J. Fabozzi, CFA,Sergio M. Focardi
• Publisher : John Wiley & Sons
• Release : 07 September 2010

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before. In order to keep up, you need a firm understanding of this discipline. Probability and Statistics for Finance addresses this issue by showing you how to apply quantitative methods to portfolios, and in all matter of your practices, in a clear, concise manner.

• Author : Kishor S. Trivedi
• Publisher : John Wiley & Sons
• Release : 30 June 2016

An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications Second edition now also available in Paperback. This updated and revised edition of the popular classic first edition relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance. This edition features an entirely new section on stochastic Petri nets—