A First Course In Probability Models And Statistical Inference

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A First Course in Probability Models and Statistical Inference

Author : James H.C. Creighton
Publisher : Springer Science & Business Media
ISBN 13 : 1441985409
Total Pages : 743 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis A First Course in Probability Models and Statistical Inference by : James H.C. Creighton

Download or read book A First Course in Probability Models and Statistical Inference written by James H.C. Creighton and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to new territory: A course in probability models and statistical inference. The concept of probability is not new to you of course. You've encountered it since childhood in games of chance-card games, for example, or games with dice or coins. And you know about the "90% chance of rain" from weather reports. But once you get beyond simple expressions of probability into more subtle analysis, it's new territory. And very foreign territory it is. You must have encountered reports of statistical results in voter sur veys, opinion polls, and other such studies, but how are conclusions from those studies obtained? How can you interview just a few voters the day before an election and still determine fairly closely how HUN DREDS of THOUSANDS of voters will vote? That's statistics. You'll find it very interesting during this first course to see how a properly designed statistical study can achieve so much knowledge from such drastically incomplete information. It really is possible-statistics works! But HOW does it work? By the end of this course you'll have understood that and much more. Welcome to the enchanted forest.

A First Course in Probability Models and Statistical Inference

Author :
Publisher : Springer
ISBN 13 : 9781441985415
Total Pages : 756 pages
Book Rating : 4.9/5 (854 download)

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Book Synopsis A First Course in Probability Models and Statistical Inference by :

Download or read book A First Course in Probability Models and Statistical Inference written by and published by Springer. This book was released on 2012-11-05 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Models for Probability and Statistical Inference

Author : James H. Stapleton
Publisher : John Wiley & Sons
ISBN 13 : 0470183403
Total Pages : 466 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Models for Probability and Statistical Inference by : James H. Stapleton

Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

A First Course in Probability

Author : Sheldon M. Ross
Publisher :
ISBN 13 :
Total Pages : 536 pages
Book Rating : 4.3/5 (97 download)

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Book Synopsis A First Course in Probability by : Sheldon M. Ross

Download or read book A First Course in Probability written by Sheldon M. Ross and published by . This book was released on 2002 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: P. 15.

Probability and Statistical Inference

Author : Miltiadis C. Mavrakakis
Publisher : CRC Press
ISBN 13 : 131536204X
Total Pages : 444 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Probability and Statistical Inference by : Miltiadis C. Mavrakakis

Download or read book Probability and Statistical Inference written by Miltiadis C. Mavrakakis and published by CRC Press. This book was released on 2021-03-29 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting. Features: •Complete introduction to mathematical probability, random variables, and distribution theory. •Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes. •Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference. •Detailed introduction to Bayesian statistics and associated topics. •Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC). This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.

Statistical Inference

Author : George Casella
Publisher : CRC Press
ISBN 13 : 1040024025
Total Pages : 1746 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Statistical Inference by : George Casella

Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 1746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.

First Course in Statistical Inference

Author : Jonathan Gillard
Publisher :
ISBN 13 : 9783030395629
Total Pages : 164 pages
Book Rating : 4.3/5 (956 download)

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Book Synopsis First Course in Statistical Inference by : Jonathan Gillard

Download or read book First Course in Statistical Inference written by Jonathan Gillard and published by . This book was released on 2020 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author's extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics.

All of Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387217363
Total Pages : 446 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis All of Statistics by : Larry Wasserman

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

A First Course in Bayesian Statistical Methods

Author : Peter D. Hoff
Publisher : Springer Science & Business Media
ISBN 13 : 0387924078
Total Pages : 271 pages
Book Rating : 4.3/5 (879 download)

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Book Synopsis A First Course in Bayesian Statistical Methods by : Peter D. Hoff

Download or read book A First Course in Bayesian Statistical Methods written by Peter D. Hoff and published by Springer Science & Business Media. This book was released on 2009-06-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.

Introduction to Probability Models

Author : Sheldon M. Ross
Publisher : Academic Press
ISBN 13 : 0123756871
Total Pages : 801 pages
Book Rating : 4.1/5 (237 download)

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Book Synopsis Introduction to Probability Models by : Sheldon M. Ross

Download or read book Introduction to Probability Models written by Sheldon M. Ross and published by Academic Press. This book was released on 2006-12-11 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text. The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students. This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes. New to this Edition: 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bank Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field Hallmark features: Superior writing style Excellent exercises and examples covering the wide breadth of coverage of probability topics Real-world applications in engineering, science, business and economics

A First Course in Probability

Author : Sheldon M. Ross
Publisher : Pearson
ISBN 13 : 9780321794772
Total Pages : 0 pages
Book Rating : 4.7/5 (947 download)

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Book Synopsis A First Course in Probability by : Sheldon M. Ross

Download or read book A First Course in Probability written by Sheldon M. Ross and published by Pearson. This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Normal 0 false false false A First Course in Probability, Ninth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary calculus. KEY TOPICS: Combinatorial Analysis; Axioms of Probability; Conditional Probability and Independence; Random Variables; Continuous Random Variables; Jointly Distributed Random Variables; Properties of Expectation; Limit Theorems; Additional Topics in Probability; Simulation MARKET: For all readers interested in probability.

A First Course in Order Statistics

Author : Barry C. Arnold
Publisher : SIAM
ISBN 13 : 0898716489
Total Pages : 291 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis A First Course in Order Statistics by : Barry C. Arnold

Download or read book A First Course in Order Statistics written by Barry C. Arnold and published by SIAM. This book was released on 2008-09-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated classic text will aid readers in understanding much of the current literature on order statistics: a flourishing field of study that is essential for any practising statistician and a vital part of the training for students in statistics. Written in a simple style that requires no advanced mathematical or statistical background, the book introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterisation results, and basic asymptotic theory. There is also a short introduction to record values and related statistics. The authors have updated the text with suggestions for further reading that may be used for self-study. Written for advanced undergraduate and graduate students in statistics and mathematics, practising statisticians, engineers, climatologists, economists, and biologists.

Probability and Statistical Inference

Author : J.G. Kalbfleisch
Publisher : Springer Science & Business Media
ISBN 13 : 1468400916
Total Pages : 321 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Probability and Statistical Inference by : J.G. Kalbfleisch

Download or read book Probability and Statistical Inference written by J.G. Kalbfleisch and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Probability Models with Optimization Applications

Author : Sheldon M. Ross
Publisher : Courier Corporation
ISBN 13 : 0486318648
Total Pages : 224 pages
Book Rating : 4.4/5 (863 download)

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Book Synopsis Applied Probability Models with Optimization Applications by : Sheldon M. Ross

Download or read book Applied Probability Models with Optimization Applications written by Sheldon M. Ross and published by Courier Corporation. This book was released on 2013-04-15 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.

Statistics for Mathematicians

Author : Victor M. Panaretos
Publisher : Birkhäuser
ISBN 13 : 3319283413
Total Pages : 177 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Statistics for Mathematicians by : Victor M. Panaretos

Download or read book Statistics for Mathematicians written by Victor M. Panaretos and published by Birkhäuser. This book was released on 2016-06-01 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.

Probability and Statistical Inference

Author : J.G. Kalbfleisch
Publisher : Springer
ISBN 13 : 9781461251361
Total Pages : 0 pages
Book Rating : 4.2/5 (513 download)

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Book Synopsis Probability and Statistical Inference by : J.G. Kalbfleisch

Download or read book Probability and Statistical Inference written by J.G. Kalbfleisch and published by Springer. This book was released on 2012-08-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is in two volumes, and is intended as a text for introductory courses in probability and statistics at the second or third year university level. It em phasizes applications and logical principles rather than mathematical theory. A good background in freshman calculus is sufficient for most of the material presented. Several starred sections have been included as supplementary material. Nearly 900 problems and exercises of varying difficulty are given, and Appendix A contains answers to about one-third of them. The first volume (Chapters 1-8) deals with probability models and with math ematical methods for describing and manipulating them. It is similar in content and organization to the 1979 edition. Some sections have been rewritten and expanded-for example, the discussions of independent random variables and conditional probability. Many new exercises have been added. In the second volume (Chapters 9-16), probability models are used as the basis for the analysis and interpretation of data. This material has been revised extensively. Chapters 9 and 10 describe the use of the likelihood function in estimation problems, as in the 1979 edition. Chapter 11 then discusses frequency properties of estimation procedures, and introduces coverage probability and confidence intervals. Chapter 12 describes tests of significance, with applications primarily to frequency data. The likelihood ratio statistic is used to unify the material on testing, and connect it with earlier material on estimation.

A First Course in Linear Model Theory

Author : Nalini Ravishanker
Publisher : CRC Press
ISBN 13 : 9781584882473
Total Pages : 494 pages
Book Rating : 4.8/5 (824 download)

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Book Synopsis A First Course in Linear Model Theory by : Nalini Ravishanker

Download or read book A First Course in Linear Model Theory written by Nalini Ravishanker and published by CRC Press. This book was released on 2001-12-21 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the mathematical and statistical concepts and tools that form a foundation for studying the theory and applications of both univariate and multivariate linear models A First Course in Linear Model Theory systematically presents the basic theory behind linear statistical models with motivation from an algebraic as well as a geometric perspective. Through the concepts and tools of matrix and linear algebra and distribution theory, it provides a framework for understanding classical and contemporary linear model theory. It does not merely introduce formulas, but develops in students the art of statistical thinking and inspires learning at an intuitive level by emphasizing conceptual understanding. The authors' fresh approach, methodical presentation, wealth of examples, and introduction to topics beyond the classical theory set this book apart from other texts on linear models. It forms a refreshing and invaluable first step in students' study of advanced linear models, generalized linear models, nonlinear models, and dynamic models.