## Introduction to Probability and Mathematical Statistics

Author: Lee J. Bain,Max Engelhardt
Publisher: Duxbury Press
ISBN: 9780534380205
Category: Mathematics
Page: 644
View: 1608

The Second Edition of INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS focuses on developing the skills to build probability (stochastic) models. Lee J. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications.

## An introduction to probability theory and mathematical statistics

Author: V. K. Rohatgi
Publisher: John Wiley & Sons Inc
ISBN: N.A
Category: Mathematics
Page: 684
View: 6681

Probability; Random variables and their probability distributions; Moments and generating functions; Random vectors; Some special distributions; Limit theorems; Sample moments and their distributions; The theory of point estimation; Neyman-Pearson theory of testing of hypotheses; Some further results on hypotheses testing; Confidence estimation; The general linear hypothesis; Nonparametric statistical inference; Sequential statistical inference.

## Introduction to Probability and Mathematical Statistics

Author: Václav Fabian
Publisher: John Wiley & Sons Incorporated
ISBN: N.A
Category: Mathematics
Page: 466
View: 5345

## An Introduction to Probability and Mathematical Statistics

Author: Howard G. Tucker
Publisher: Academic Press
ISBN: 1483225143
Category: Mathematics
Page: 240
View: 696

An Introduction to Probability and Mathematical Statistics provides information pertinent to the fundamental aspects of probability and mathematical statistics. This book covers a variety of topics, including random variables, probability distributions, discrete distributions, and point estimation. Organized into 13 chapters, this book begins with an overview of the definition of function. This text then examines the notion of conditional or relative probability. Other chapters consider Cochran's theorem, which is of extreme importance in that part of statistical inference known as analysis of variance. This book discusses as well the fundamental principles of testing statistical hypotheses by providing the reader with an idea of the basic problem and its relation to practice. The final chapter deals with the problem of estimation and the Neyman theory of confidence intervals. This book is a valuable resource for undergraduate university students who are majoring in mathematics. Students who are majoring in physics and who are inclined toward abstract mathematics will also find this book useful.

## An Introduction to Probability and Statistics

Author: Vijay K. Rohatgi,A.K. Md. Ehsanes Saleh
Publisher: John Wiley & Sons
ISBN: 1118799682
Category: Mathematics
Page: 728
View: 4867

A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over 550 problems and answers to most problems, as well as 350 worked out examples and 200 remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.

## Probability and Mathematical Statistics

An Introduction
Author: Eugene Lukacs
Publisher: Academic Press
ISBN: 1483269205
Category: Mathematics
Page: 254
View: 3104

Probability and Mathematical Statistics: An Introduction provides a well-balanced first introduction to probability theory and mathematical statistics. This book is organized into two sections encompassing nine chapters. The first part deals with the concept and elementary properties of probability space, and random variables and their probability distributions. This part also considers the principles of limit theorems, the distribution of random variables, and the so-called student’s distribution. The second part explores pertinent topics in mathematical statistics, including the concept of sampling, estimation, and hypotheses testing. This book is intended primarily for undergraduate statistics students.

## An Introduction to Probability and Mathematical Statistics

Author: Lee J. Bain,Cram101 Textbook Reviews,Max Engelhardt
Publisher: Academic Internet Pub Incorporated
ISBN: 9781428814318
Category: Education
Page: 88
View: 802

Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780534380205 9780534929305 .

## Introduction to Probability and Statistics for Engineers

Author: Milan Holický
Publisher: Springer Science & Business Media
ISBN: 3642383009
Category: Mathematics
Page: 181
View: 2979

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 and tests of statistical hypotheses. Basic concepts of Bayesian approach to probability and two-dimensional random variables, are also covered. Examples of reliability analysis and risk assessment of technological systems are used throughout the book to illustrate basic theoretical concepts and their applications. The primary audience for the book includes undergraduate and graduate students of science and engineering, scientific workers and engineers and specialists in the field of reliability analysis and risk assessment. Except basic knowledge of undergraduate mathematics no special prerequisite is required.

## Introduction to Probability with Statistical Applications

Author: Géza Schay
Publisher: Birkhäuser
ISBN: 3319306200
Category: Mathematics
Page: 385
View: 394

Now in its second edition, this textbook serves as an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. More classical examples such as Montmort's problem, the ballot problem, and Bertrand’s paradox are now included, along with applications such as the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features in new edition: * 35 new exercises * Expanded section on the algebra of sets * Expanded chapters on probabilities to include more classical examples * New section on regression * Online instructors' manual containing solutions to all exercises“/p> Advanced undergraduate and graduate students in computer science, engineering, and other natural and social sciences with only a basic background in calculus will benefit from this introductory text balancing theory with applications. Review of the first edition: This textbook is a classical and well-written introduction to probability theory and statistics. ... the book is written ‘for an audience such as computer science students, whose mathematical background is not very strong and who do not need the detail and mathematical depth of similar books written for mathematics or statistics majors.’ ... Each new concept is clearly explained and is followed by many detailed examples. ... numerous examples of calculations are given and proofs are well-detailed." (Sophie Lemaire, Mathematical Reviews, Issue 2008 m)

## Einführung in Die Mathematische Statistik

Author: Leopold Schmetterer
Publisher: Springer-Verlag
ISBN: 3662259338
Category: Mathematics
Page: 597
View: 5391

Die Frage nach dem Aufgabenkreis der Statistik im allgemeinen kann nicht mit wenigen Worten umrissen werden. Wenn man etwas näher auf die geschichtliche Entwicklung des Begriffes Statistik eingeht\ so findet man, daß lange Zeit darunter nur die Beschrei bung von "Staatsmerkwürdigkeiten" (wie Bevölkerungszahl, Bo denbeschaffenheit, Sammlung wirtschaftlicher Daten) verstanden wurde. Erst in neuerer Zeit drang die statistische Betrachtungsweise auch in die Naturwissenschaften ein (BOLTZMANN, GIBBS, MAx WELL). Fußend auf dem Boden der seit Beginn dieses Jahrhunderts sich rasch entwickelnden Wahrscheinlichkeitstheorie hat dann ins besondere in den letzten dreißig Jahren auch die mathematische Statistik einen unerhörten Aufschwung genommen und die Metho den der statistischen Analyse mit einer kaum zu übersehenden Fülle von Gedanken bereichert. Statistische Überlegungen treten heute in den verschiedensten Wissensgebieten auf. Es genügt, wenn wir neben den Wirtschaftswissenschaften als Beispiele die Astronomie, die Biologie, die Medizin, die Psychologie, die Physik und die Soziologie anführen. Wenn es also, wie gesagt, nicht leicht ist, den allgemeinen Be griff der Statistik kurz zu charakterisieren, so geht man doch wohl nicht fehl, wenn man feststellt, daß sich die Statistik mit dem Studium von Erscheinungen befaßt, die entweder eine große Zahl von Individuen betreffen, oder sonst in irgendeiner Weise eine Viel falt von Einzelerscheinungen zusammenfassen. Man kann somit als ein Charakteristikum der Statistik das Studium der Massen erscheinungen betrachten. Es ist eine Erfahrungstatsache, daß bei Massenerscheinungen Gesetzmäßigkeiten nachgewiesen werden können, die bei Einzelerscheinungen kein Gegenstück haben. Das 1 Vgl. W. WrNKLER, Grundriß der Statistik I, 2.

## Stochastik

Einführung in die Wahrscheinlichkeitstheorie und Statistik
Author: Hans-Otto Georgii
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110386860
Category: Mathematics
Page: 448
View: 8579

Due to the extremely positive reception of this textbook, it is now being published in its 5th edition. The book provides an introduction to the key ideas and elements of probability theory and statistics. Stochastic concepts, models, and methods are highlighted through typical application examples, then analyzed theoretically and systematically explored.

## Mathematical Statistics with Applications in R

Author: Kandethody M. Ramachandran,Chris P. Tsokos
Publisher: Elsevier
ISBN: 012417132X
Category: Mathematics
Page: 826
View: 7637

Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

## Student Solutions Manual

An Introduction to Mathematical Statistics and Its Applications
Author: Richard J. Larsen,Morris L. Marx
Publisher: Prentice Hall
ISBN: N.A
Category: Education
Page: 121
View: 3649

## An introduction to mathematical statistics

Author: F. Bijma,M. Jonker,A. van der Vaart
Publisher: Amsterdam University Press
ISBN: 9048536111
Category: Mathematics
Page: N.A
View: 8568

Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models. In An Introduction to Mathematical Statistics the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data. The three main topics in statistics are estimators, tests, and confidence regions. The authors illustrate these in many examples, with a separate chapter on regression models, including linear regression and analysis of variance. They also discuss the optimality of estimators and tests, as well as the selection of the best-fitting model. Each chapter ends with a case study in which the described statistical methods are applied. This book assumes a basic knowledge of probability theory, calculus, and linear algebra.

## Introduction to Probability and Statistics from a Bayesian Viewpoint, Part 1, Probability

Author: D. V. Lindley
Publisher: CUP Archive
ISBN: 9780521298674
Category: Mathematics
Page: 272
View: 3748

The two parts of this book treat probability and statistics as mathematical disciplines and with the same degree of rigour as is adopted for other branches of applied mathematics at the level of a British honours degree. They contain the minimum information about these subjects that any honours graduate in mathematics ought to know. They are written primarily for general mathematicians, rather than for statistical specialists or for natural scientists who need to use statistics in their work. No previous knowledge of probability or statistics is assumed, though familiarity with calculus and linear algebra is required. The first volume takes the theory of probability sufficiently far to be able to discuss the simpler random processes, for example, queueing theory and random walks. The second volume deals with statistics, the theory of making valid inferences from experimental data, and includes an account of the methods of least squares and maximum likelihood; it uses the results of the first volume.

## A Modern Introduction to Probability and Statistics

Understanding Why and How
Author: F.M. Dekking,C. Kraaikamp,H.P. Lopuhaä,L.E. Meester
Publisher: Springer Science & Business Media
ISBN: 1846281687
Category: Mathematics
Page: 488
View: 9454

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

## Introduction to Probability and Statistics for Engineers and Scientists

Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0123948428
Category: Mathematics
Page: 686
View: 9004

Introduction to Probability and Statistics for Engineers and Scientists provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations. Clear exposition by a renowned expert author Real data examples that use significant real data from actual studies across life science, engineering, computing and business End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material 25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science New additions to proofs in the estimation section New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

## An introduction to probability theory and its applications

Author: William Feller
Publisher: John Wiley & Sons Inc
ISBN: N.A
Category: Business & Economics
Page: 704
View: 8212

Major changes in this edition include the substitution of probabilistic arguments for combinatorial artifices, and the addition of new sections on branching processes, Markov chains, and the De Moivre-Laplace theorem.

## An Introduction to Probability and Statistical Inference

Author: George G. Roussas
Publisher: Academic Press
ISBN: 0128004371
Category: Mathematics
Page: 624
View: 5889

An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual. This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture. Content, examples, an enhanced number of exercises, and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities Reorganized material in the statistical portion of the book to ensure continuity and enhance understanding A relatively rigorous, yet accessible and always within the prescribed prerequisites, mathematical discussion of probability theory and statistical inference important to students in a broad variety of disciplines Relevant proofs where appropriate in each section, followed by exercises with useful clues to their solutions Brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises available to instructors in an Answers Manual