Fundamentals of Mathematical Statistics

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Publisher : Springer Science & Business Media
ISBN 13 : 1461210135
Total Pages : 442 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Fundamentals of Mathematical Statistics by : Hung T. Nguyen

Download or read book Fundamentals of Mathematical Statistics written by Hung T. Nguyen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first half of a text for a two semester course in mathematical statistics at the senior/graduate level for those who need a strong background in statistics as an essential tool in their career. To study this text, the reader needs a thorough familiarity with calculus including such things as Jacobians and series but somewhat less intense familiarity with matrices including quadratic forms and eigenvalues. For convenience, these lecture notes were divided into two parts: Volume I, Probability for Statistics, for the first semester, and Volume II, Statistical Inference, for the second. We suggest that the following distinguish this text from other introductions to mathematical statistics. 1. The most obvious thing is the layout. We have designed each lesson for the (U.S.) 50 minute class; those who study independently probably need the traditional three hours for each lesson. Since we have more than (the U.S. again) 90 lessons, some choices have to be made. In the table of contents, we have used a * to designate those lessons which are "interesting but not essential" (INE) and may be omitted from a general course; some exercises and proofs in other lessons are also "INE". We have made lessons of some material which other writers might stuff into appendices. Incorporating this freedom of choice has led to some redundancy, mostly in definitions, which may be beneficial.

Essentials of Mathematical Statistics

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Publisher : Jones & Bartlett Publishers
ISBN 13 : 144968534X
Total Pages : 607 pages
Book Rating : 4.4/5 (496 download)

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Book Synopsis Essentials of Mathematical Statistics by : Brian Albright

Download or read book Essentials of Mathematical Statistics written by Brian Albright and published by Jones & Bartlett Publishers. This book was released on 2014 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.

Fundamentals of Statistics with Fuzzy Data

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Publisher : Springer
ISBN 13 : 3540316973
Total Pages : 0 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Fundamentals of Statistics with Fuzzy Data by : Hung T. Nguyen

Download or read book Fundamentals of Statistics with Fuzzy Data written by Hung T. Nguyen and published by Springer. This book was released on 2006-02-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.

Fundamentals of Mathematical Statistics

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Publisher : Sultan Chand & Sons
ISBN 13 : 9351611736
Total Pages : 22 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Fundamentals of Mathematical Statistics by : S.C. Gupta

Download or read book Fundamentals of Mathematical Statistics written by S.C. Gupta and published by Sultan Chand & Sons. This book was released on 2020-09-10 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Some prominent additions are given below: 1. Variance of Degenerate Random Variable 2. Approximate Expression for Expectation and Variance 3. Lyapounov’s Inequality 4. Holder’s Inequality 5. Minkowski’s Inequality 6. Double Expectation Rule or Double-E Rule and many others

Fundamentals of Mathematical Statistics

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (489 download)

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Book Synopsis Fundamentals of Mathematical Statistics by : Hung T. Nguyen

Download or read book Fundamentals of Mathematical Statistics written by Hung T. Nguyen and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fundamentals of Mathematical Statistics

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Publisher : Springer
ISBN 13 :
Total Pages : 448 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Fundamentals of Mathematical Statistics by : Hung T. Nguyen

Download or read book Fundamentals of Mathematical Statistics written by Hung T. Nguyen and published by Springer. This book was released on 1989-07-25 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a text (divided into two volumes) for a two semester course in Mathematical Statistics at the Senior/Graduate level. The two main pedagogical aspects in these Volumes are: (i) the material is designed in lessons (each for a 50 minute class) with complementary exercises and home work. (ii) although the material is traditional, great care is exerted upon self-contained, rigorous and complete presentations. An elementary introduction to characteristic functions and probability measures and intergration, but not general measure theory in Volume I, allows a complete proof of some central limit theorems and a rigorous treatment of asymptotic of statistical inference. But students need to be familiar only with such things as Jacobians and eigenvalues of matrices. Volume II: Statistical Inference is designed for the second semester and contains a rigorous introduction to Mathematical Statistics, from random samples to asymptotic theory of statistical inference.

Mathematical Statistics

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Publisher : John Wiley & Sons
ISBN 13 : 1119385237
Total Pages : 886 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis Mathematical Statistics by : Dieter Rasch

Download or read book Mathematical Statistics written by Dieter Rasch and published by John Wiley & Sons. This book was released on 2018-01-09 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores mathematical statistics in its entirety—from the fundamentals to modern methods This book introduces readers to point estimation, confidence intervals, and statistical tests. Based on the general theory of linear models, it provides an in-depth overview of the following: analysis of variance (ANOVA) for models with fixed, random, and mixed effects; regression analysis is also first presented for linear models with fixed, random, and mixed effects before being expanded to nonlinear models; statistical multi-decision problems like statistical selection procedures (Bechhofer and Gupta) and sequential tests; and design of experiments from a mathematical-statistical point of view. Most analysis methods have been supplemented by formulae for minimal sample sizes. The chapters also contain exercises with hints for solutions. Translated from the successful German text, Mathematical Statistics requires knowledge of probability theory (combinatorics, probability distributions, functions and sequences of random variables), which is typically taught in the earlier semesters of scientific and mathematical study courses. It teaches readers all about statistical analysis and covers the design of experiments. The book also describes optimal allocation in the chapters on regression analysis. Additionally, it features a chapter devoted solely to experimental designs. Classroom-tested with exercises included Practice-oriented (taken from day-to-day statistical work of the authors) Includes further studies including design of experiments and sample sizing Presents and uses IBM SPSS Statistics 24 for practical calculations of data Mathematical Statistics is a recommended text for advanced students and practitioners of math, probability, and statistics.

Fundamentals of Probability and Statistics for Engineers

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Publisher : John Wiley & Sons
ISBN 13 : 0470868155
Total Pages : 406 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Fundamentals of Probability and Statistics for Engineers by : T. T. Soong

Download or read book Fundamentals of Probability and Statistics for Engineers written by T. T. Soong and published by John Wiley & Sons. This book was released on 2004-06-25 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.

Mathematical Theory of Probability and Statistics

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Publisher : Academic Press
ISBN 13 : 1483264025
Total Pages : 708 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Mathematical Theory of Probability and Statistics by : Richard von Mises

Download or read book Mathematical Theory of Probability and Statistics written by Richard von Mises and published by Academic Press. This book was released on 2014-05-12 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Theory of Probability and Statistics focuses on the contributions and influence of Richard von Mises on the processes, methodologies, and approaches involved in the mathematical theory of probability and statistics. The publication first elaborates on fundamentals, general label space, and basic properties of distributions. Discussions focus on Gaussian distribution, Poisson distribution, mean value variance and other moments, non-countable label space, basic assumptions, operations, and distribution function. The text then ponders on examples of combined operations and summation of chance variables characteristic function. The book takes a look at the asymptotic distribution of the sum of chance variables and probability inference. Topics include inference from a finite number of observations, law of large numbers, asymptotic distributions, limit distribution of the sum of independent discrete random variables, probability of the sum of rare events, and probability density. The text also focuses on the introduction to the theory of statistical functions and multivariate statistics. The publication is a dependable source of information for researchers interested in the mathematical theory of probability and statistics

Fundamentals of Mathematical Statistics: Probability for statistics

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Publisher :
ISBN 13 : 9787506210966
Total Pages : 432 pages
Book Rating : 4.2/5 (19 download)

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Book Synopsis Fundamentals of Mathematical Statistics: Probability for statistics by :

Download or read book Fundamentals of Mathematical Statistics: Probability for statistics written by and published by . This book was released on 1991 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Foundations of Mathematics and Statistics

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Publisher :
ISBN 13 : 9781546277484
Total Pages : 538 pages
Book Rating : 4.2/5 (774 download)

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Book Synopsis Foundations of Mathematics and Statistics by : Timothy C. Kearns

Download or read book Foundations of Mathematics and Statistics written by Timothy C. Kearns and published by . This book was released on 2019-01-26 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Mathematics and Statistics is a summary of the basic principles of math and statistics for students that are interested in pursuing studies in the mathematical sciences. The first goal is to provide a good foundation of knowledge and ability with the basics of mathematics. This includes logic, sets, number systems, algebra, geometry, trigonometry, and the calculus. Then the remainder of the book deals with the fundamental topics of applied and mathematical statistics, including probability, random variables, expected value, samples, distributions, hypothesis testing, confidence intervals, and an introduction to linear regression and correlation. The book can be used by all students that need a summary of math fundamentals, with a sound introduction to the basics of statistical thinking and methodology. Those that need a good familiarity with math and statistics would find this book a valuable supplemental reading, along with the fair amount of exercises that are included in order to reinforce the important ideas.

Examples and Problems in Mathematical Statistics

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Publisher : John Wiley & Sons
ISBN 13 : 1118605837
Total Pages : 652 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Examples and Problems in Mathematical Statistics by : Shelemyahu Zacks

Download or read book Examples and Problems in Mathematical Statistics written by Shelemyahu Zacks and published by John Wiley & Sons. This book was released on 2013-12-17 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features: Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving More than 430 unique exercises with select solutions Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.

A Modern Introduction to Probability and Statistics

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Publisher : Springer Science & Business Media
ISBN 13 : 1846281687
Total Pages : 488 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis A Modern Introduction to Probability and Statistics by : F.M. Dekking

Download or read book A Modern Introduction to Probability and Statistics written by F.M. Dekking and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Mathematical Statistics

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Publisher : John Wiley & Sons
ISBN 13 : 1118771168
Total Pages : 623 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Mathematical Statistics by : Richard J. Rossi

Download or read book Mathematical Statistics written by Richard J. Rossi and published by John Wiley & Sons. This book was released on 2018-06-14 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and first year graduate students, tying chapters on estimation, confidence intervals, hypothesis testing, and statistical models together to present a unifying focus on the likelihood function. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large sample properties. Mathematical Statistics: An Introduction to Likelihood Based Inference makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks. It includes numerous examples, case studies, a large number of exercises ranging from drill and skill to extremely difficult problems, and many of the important theorems of mathematical statistics along with their proofs. In addition to the connected chapters mentioned above, Mathematical Statistics covers likelihood-based estimation, with emphasis on multidimensional parameter spaces and range dependent support. It also includes a chapter on confidence intervals, which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE's and bootstrap confidence intervals. There’s also a chapter on parametric statistical models featuring sections on non-iid observations, linear regression, logistic regression, Poisson regression, and linear models. Prepares students with the tools needed to be successful in their future work in statistics data science Includes practical case studies including real-life data collected from Yellowstone National Park, the Donner party, and the Titanic voyage Emphasizes the important ideas to statistical modeling, such as sufficiency, exponential family distributions, and large sample properties Includes sections on Bayesian estimation and credible intervals Features examples, problems, and solutions Mathematical Statistics: An Introduction to Likelihood Based Inference is an ideal textbook for upper-undergraduate and graduate courses in probability, mathematical statistics, and/or statistical inference.

Fundamentals of mathematical statistics

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Publisher :
ISBN 13 : 9787506210973
Total Pages : 422 pages
Book Rating : 4.2/5 (19 download)

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Book Synopsis Fundamentals of mathematical statistics by : Hung T. Nguyen

Download or read book Fundamentals of mathematical statistics written by Hung T. Nguyen and published by . This book was released on 1991 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modern Concepts and Theorems of Mathematical Statistics

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Publisher : Springer Science & Business Media
ISBN 13 : 1461248566
Total Pages : 168 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Modern Concepts and Theorems of Mathematical Statistics by : Edward B. Manoukian

Download or read book Modern Concepts and Theorems of Mathematical Statistics written by Edward B. Manoukian and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid progress and development of mathematical statistical methods, it is becoming more and more important for the student, the in structor, and the researcher in this field to have at their disposal a quick, comprehensive, and compact reference source on a very wide range of the field of modern mathematical statistics. This book is an attempt to fulfill this need and is encyclopedic in nature. It is a useful reference for almost every learner involved with mathematical statistics at any level, and may supple ment any textbook on the subject. As the primary audience of this book, we have in mind the beginning busy graduate student who finds it difficult to master basic modern concepts by an examination of a limited number of existing textbooks. To make the book more accessible to a wide range of readers I have kept the mathematical language at a level suitable for those who have had only an introductory undergraduate course on probability and statistics, and basic courses in calculus and linear algebra. No sacrifice, how ever, is made to dispense with rigor. In stating theorems I have not always done so under the weakest possible conditions. This allows the reader to readily verify if such conditions are indeed satisfied in most applications given in modern graduate courses without being lost in extra unnecessary mathematical intricacies. The book is not a mere dictionary of mathematical statistical terms.

Probability for Statistics and Machine Learning

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Publisher : Springer Science & Business Media
ISBN 13 : 1441996346
Total Pages : 796 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Probability for Statistics and Machine Learning by : Anirban DasGupta

Download or read book Probability for Statistics and Machine Learning written by Anirban DasGupta and published by Springer Science & Business Media. This book was released on 2011-05-17 with total page 796 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.