Advertisement
| an introduction to mathematical statistics and its applications: Introduction to Mathematical Statistics and Its Applications Richard J. Larsen, Morris L. Marx, 2013-08-28 Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout the 5th Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. |
| an introduction to mathematical statistics and its applications: An Introduction to Mathematical Statistics and Its Applications Richard J. Larsen, Morris L. Marx, 2006 Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. It demonstrates how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. |
| an introduction to mathematical statistics and its applications: Introduction to Mathematical Statistics and Its Applications Richard Larsen, |
| an introduction to mathematical statistics and its applications: Introduction to Mathematical Statistics, Fifth Edition Robert V. Hogg, Allen Thornton Craig, 1995 |
| an introduction to mathematical statistics and its applications: Introduction to Mathematical Statistics and Its Applications Richard J. Larsen, Morris L. Marx, 2013-07-29 Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics with Applications in R Kandethody M. Ramachandran, Chris P. Tsokos, 2014-09-14 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 |
| an introduction to mathematical statistics and its applications: Modern Mathematical Statistics with Applications Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton, 2021-04-29 This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline. |
| an introduction to mathematical statistics and its applications: All of Statistics Larry Wasserman, 2013-12-11 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. |
| an introduction to mathematical statistics and its applications: Matrix Analysis and Applied Linear Algebra Carl D. Meyer, 2000-06-01 This book avoids the traditional definition-theorem-proof format; instead a fresh approach introduces a variety of problems and examples all in a clear and informal style. The in-depth focus on applications separates this book from others, and helps students to see how linear algebra can be applied to real-life situations. Some of the more contemporary topics of applied linear algebra are included here which are not normally found in undergraduate textbooks. Theoretical developments are always accompanied with detailed examples, and each section ends with a number of exercises from which students can gain further insight. Moreover, the inclusion of historical information provides personal insights into the mathematicians who developed this subject. The textbook contains numerous examples and exercises, historical notes, and comments on numerical performance and the possible pitfalls of algorithms. Solutions to all of the exercises are provided, as well as a CD-ROM containing a searchable copy of the textbook. |
| an introduction to mathematical statistics and its applications: Stat Labs Deborah Nolan, Terry P. Speed, 2006-05-02 Integrating the theory and practice of statistics through a series of case studies, each lab introduces a problem, provides some scientific background, suggests investigations for the data, and provides a summary of the theory used in each case. Aimed at upper-division students. |
| an introduction to mathematical statistics and its applications: Fundamentals of Mathematical Statistics S.C. Gupta, V.K. Kapoor, 2020-09-10 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 |
| an introduction to mathematical statistics and its applications: Introduction to the Mathematical and Statistical Foundations of Econometrics Herman J. Bierens, 2004-12-20 This book is intended for use in a rigorous introductory PhD level course in econometrics. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics Jun Shao, 2008-02-03 This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics Wiebe R. Pestman, 2009-03-26 This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented. |
| an introduction to mathematical statistics and its applications: An Introduction to Mathematical Statistics Fetsje Bijma, Marianne Jonker, A. W. van der Vaart, 2017 This book gives an introduction into mathematical statistics. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics Dieter Rasch, Dieter Schott, 2018-03-19 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. |
| an introduction to mathematical statistics and its applications: Statistics for Mathematicians Victor M. Panaretos, 2016-06-01 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. |
| an introduction to mathematical statistics and its applications: Introduction to Probability and Mathematical Statistics Lee J. Bain, Max Engelhardt, 2000-03-01 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 mathematical statistics and its applications: Student Solutions Manual Richard J. Larsen, 2001 |
| an introduction to mathematical statistics and its applications: Mathematical Statistics with Applications Dennis Wackerly, William Mendenhall, Richard L. Scheaffer, 2014-10-27 In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |
| an introduction to mathematical statistics and its applications: High-Dimensional Probability Roman Vershynin, 2018-09-27 An integrated package of powerful probabilistic tools and key applications in modern mathematical data science. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics for Economics and Business Ron C. Mittelhammer, 2013-03-14 Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics. The selection of topics in this textbook is designed to provide students with a conceptual foundation that will facilitate a substantial understanding of statistical applications in these subjects. This new edition has been updated throughout and now also includes a downloadable Student Answer Manual containing detailed solutions to half of the over 300 end-of-chapter problems. After introducing the concepts of probability, random variables, and probability density functions, the author develops the key concepts of mathematical statistics, most notably: expectation, sampling, asymptotics, and the main families of distributions. The latter half of the book is then devoted to the theories of estimation and hypothesis testing with associated examples and problems that indicate their wide applicability in economics and business. Features of the new edition include: a reorganization of topic flow and presentation to facilitate reading and understanding; inclusion of additional topics of relevance to statistics and econometric applications; a more streamlined and simple-to-understand notation for multiple integration and multiple summation over general sets or vector arguments; updated examples; new end-of-chapter problems; a solution manual for students; a comprehensive answer manual for instructors; and a theorem and definition map. This book has evolved from numerous graduate courses in mathematical statistics and econometrics taught by the author, and will be ideal for students beginning graduate study as well as for advanced undergraduates. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics With Applications Asha Seth Kapadia, Wenyaw Chan, Lemuel A. Moyé, 2005-04-20 Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds. Most textbooks on the subject provide little or no review of the advanced calculus topics upon which much of mathematical statistics relies and furthermore contain material that is wholly theoretical, thus presenting even greater challenges to those interested in applying advanced statistics to a specific area. Mathematical Statistics with Applications presents the background concepts and builds the technical sophistication needed to move on to more advanced studies in multivariate analysis, decision theory, stochastic processes, or computational statistics. Applications embedded within theoretical discussions clearly demonstrate the utility of the theory in a useful and relevant field of application and allow readers to avoid sudden exposure to purely theoretical materials. With its clear explanations and more than usual emphasis on applications and computation, this text reaches out to the many students and professionals more interested in the practical use of statistics to enrich their work in areas such as communications, computer science, economics, astronomy, and public health. |
| an introduction to mathematical statistics and its applications: Statistics for High-Dimensional Data Peter Bühlmann, Sara van de Geer, 2011-06-08 Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science. |
| an introduction to mathematical statistics and its applications: Statistics Richard J. Larsen, Morris L. Marx, 1990 Appropriate for the algebra-based statistics course. First AIE for its market, extensive use of computers within text, includes case studies throughout. |
| an introduction to mathematical statistics and its applications: Introduction to Probability with Statistical Applications Géza Schay, 2016-06-17 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) |
| an introduction to mathematical statistics and its applications: Introduction to Probability David F. Anderson, Timo Seppäläinen, Benedek Valkó, 2017-11-02 This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work. |
| an introduction to mathematical statistics and its applications: Statistical Mechanics of Lattice Systems Sacha Friedli, Yvan Velenik, 2017-11-23 A self-contained, mathematical introduction to the driving ideas in equilibrium statistical mechanics, studying important models in detail. |
| an introduction to mathematical statistics and its applications: An Introduction to Kolmogorov Complexity and Its Applications Ming Li, Paul Vitanyi, 2013-03-09 Briefly, we review the basic elements of computability theory and prob ability theory that are required. Finally, in order to place the subject in the appropriate historical and conceptual context we trace the main roots of Kolmogorov complexity. This way the stage is set for Chapters 2 and 3, where we introduce the notion of optimal effective descriptions of objects. The length of such a description (or the number of bits of information in it) is its Kolmogorov complexity. We treat all aspects of the elementary mathematical theory of Kolmogorov complexity. This body of knowledge may be called algo rithmic complexity theory. The theory of Martin-Lof tests for random ness of finite objects and infinite sequences is inextricably intertwined with the theory of Kolmogorov complexity and is completely treated. We also investigate the statistical properties of finite strings with high Kolmogorov complexity. Both of these topics are eminently useful in the applications part of the book. We also investigate the recursion theoretic properties of Kolmogorov complexity (relations with Godel's incompleteness result), and the Kolmogorov complexity version of infor mation theory, which we may call algorithmic information theory or absolute information theory. The treatment of algorithmic probability theory in Chapter 4 presup poses Sections 1. 6, 1. 11. 2, and Chapter 3 (at least Sections 3. 1 through 3. 4). |
| an introduction to mathematical statistics and its applications: Mathematical Statistics Keith Knight, 1999-11-24 Traditional texts in mathematical statistics can seem - to some readers-heavily weighted with optimality theory of the various flavors developed in the 1940s and50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of useful tools that allow students to understand the theoretical underpinnings of statistical methodology. The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that models are often incorrectly specified - he also views estimation from a non-parametric perspective. Overall, Mathematical Statistics places greater emphasis on frequentist methodology than on Bayesian, but claims no particular superiority for that approach. It does emphasize, however, the utility of statistical and mathematical software packages, and includes several sections addressing computational issues. The result reaches beyond nice mathematics to provide a balanced, practical text that brings life and relevance to a subject so often perceived as irrelevant and dry. |
| an introduction to mathematical statistics and its applications: Statistics and Probability with Applications (High School) Daren Starnes, Josh Tabor, 2016-10-07 Statistics and Probability with Applications, Third Edition is the only introductory statistics text written by high school teachers for high school teachers and students. Daren Starnes, Josh Tabor, and the extended team of contributors bring their in-depth understanding of statistics and the challenges faced by high school students and teachers to development of the text and its accompanying suite of print and interactive resources for learning and instruction. A complete re-envisioning of the authors’ Statistics Through Applications, this new text covers the core content for the course in a series of brief, manageable lessons, making it easy for students and teachers to stay on pace. Throughout, new pedagogical tools and lively real-life examples help captivate students and prepare them to use statistics in college courses and in any career. |
| an introduction to mathematical statistics and its applications: An Introduction to the Theory of Point Processes D.J. Daley, D. Vere-Jones, 2006-04-10 Point processes and random measures find wide applicability in telecommunications, earthquakes, image analysis, spatial point patterns, and stereology, to name but a few areas. The authors have made a major reshaping of their work in their first edition of 1988 and now present their Introduction to the Theory of Point Processes in two volumes with sub-titles Elementary Theory and Models and General Theory and Structure. Volume One contains the introductory chapters from the first edition, together with an informal treatment of some of the later material intended to make it more accessible to readers primarily interested in models and applications. The main new material in this volume relates to marked point processes and to processes evolving in time, where the conditional intensity methodology provides a basis for model building, inference, and prediction. There are abundant examples whose purpose is both didactic and to illustrate further applications of the ideas and models that are the main substance of the text. |
| an introduction to mathematical statistics and its applications: Mathematical Statistics and Data Analysis John A. Rice, 2007 This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings. |
| an introduction to mathematical statistics and its applications: John E. Freund's Mathematical Statistics with Applications Irwin Miller, Marylees Miller, 2015-12-03 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices. |
| an introduction to mathematical statistics and its applications: An Introduction to Probability and Statistics Vijay K. Rohatgi, A. K. Md. Ehsanes Saleh, 2015-09-01 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. |
| an introduction to mathematical statistics and its applications: Classic Topics on the History of Modern Mathematical Statistics Prakash Gorroochurn, 2016-03-29 There is nothing like it on the market...no others are as encyclopedic...the writing is exemplary: simple, direct, and competent. —George W. Cobb, Professor Emeritus of Mathematics and Statistics, Mount Holyoke College Written in a direct and clear manner, Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times presents a comprehensive guide to the history of mathematical statistics and details the major results and crucial developments over a 200-year period. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. Divided into three parts, the book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistical theory. Subsequently, the second part introduces 20th century statistical developments including work from Karl Pearson, Student, Fisher, and Neyman. Lastly, the author addresses post-Fisherian developments. Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times also features: A detailed account of Galton's discovery of regression and correlation as well as the subsequent development of Karl Pearson's X2 and Student's t A comprehensive treatment of the permeating influence of Fisher in all aspects of modern statistics beginning with his work in 1912 Significant coverage of Neyman–Pearson theory, which includes a discussion of the differences to Fisher’s works Discussions on key historical developments as well as the various disagreements, contrasting information, and alternative theories in the history of modern mathematical statistics in an effort to provide a thorough historical treatment Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times is an excellent reference for academicians with a mathematical background who are teaching or studying the history or philosophical controversies of mathematics and statistics. The book is also a useful guide for readers with a general interest in statistical inference. |
| an introduction to mathematical statistics and its applications: A Course in Mathematical Statistics and Large Sample Theory Rabi Bhattacharya, Lizhen Lin, Victor Patrangenaru, 2016-08-13 This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods. |
| an introduction to mathematical statistics and its applications: Statistics of Financial Markets Szymon Borak, Wolfgang Karl Härdle, Brenda López-Cabrera, 2013-01-11 Practice makes perfect. Therefore the best method of mastering models is working with them. This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123. The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges. |
| an introduction to mathematical statistics and its applications: Student's Solutions Manual for an Introduction to Mathematical Statistics and Its Applications Richard J. Larsen, Morris L. Marx, 2017-02-28 This manual contains completely worked-out solutions for all the odd-numbered exercises in the text. |
| an introduction to mathematical statistics and its applications: Lectures on Probability Theory and Mathematical Statistics - 3rd Edition Marco Taboga, 2017-12-08 The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. There are hundreds of examples, solved exercises and detailed derivations of important results. The step-by-step approach makes the book easy to understand and ideal for self-study. One of the main aims of the book is to be a time saver: it contains several results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books. The topics covered by the book are as follows. PART 1 - MATHEMATICAL TOOLS: set theory, permutations, combinations, partitions, sequences and limits, review of differentiation and integration rules, the Gamma and Beta functions. PART 2 - FUNDAMENTALS OF PROBABILITY: events, probability, independence, conditional probability, Bayes' rule, random variables and random vectors, expected value, variance, covariance, correlation, covariance matrix, conditional distributions and conditional expectation, independent variables, indicator functions. PART 3 - ADDITIONAL TOPICS IN PROBABILITY THEORY: probabilistic inequalities, construction of probability distributions, transformations of probability distributions, moments and cross-moments, moment generating functions, characteristic functions. PART 4 - PROBABILITY DISTRIBUTIONS: Bernoulli, binomial, Poisson, uniform, exponential, normal, Chi-square, Gamma, Student's t, F, multinomial, multivariate normal, multivariate Student's t, Wishart. PART 5 - MORE DETAILS ABOUT THE NORMAL DISTRIBUTION: linear combinations, quadratic forms, partitions. PART 6 - ASYMPTOTIC THEORY: sequences of random vectors and random variables, pointwise convergence, almost sure convergence, convergence in probability, mean-square convergence, convergence in distribution, relations between modes of convergence, Laws of Large Numbers, Central Limit Theorems, Continuous Mapping Theorem, Slutsky's Theorem. PART 7 - FUNDAMENTALS OF STATISTICS: statistical inference, point estimation, set estimation, hypothesis testing, statistical inferences about the mean, statistical inferences about the variance. |
怎样写好英文论文的 Introduction 部分呢？ - 知乎
Introduction应该是一篇论文中最难写的一部分，也是最重要的。“A good introduction will “sell” the study to editors, reviewers, readers, and sometimes even the media.” [1]。通过Introduction可以 …
怎样写好英文论文的 Introduction 部分？ - 知乎
Why An Introduction Is Needed？ 「从文章的大结构来看Introduction提出了你的研究问题，这个问题的答案应该在文章的Discussion或者Conclusion部分呈现给读者，也就是在文章的首尾形成一个前后 …
Difference between "introduction to" and "introduction of"
May 22, 2011 · Here, "Introduction of" refers to bringing something into a place or situation. "Can you give me an introduction to the president of the company?" "Introduction to" is more …
科学引文索引（SCI）论文的引言（Introduction）怎么写？ - 知乎
Introduction一共分为8段，属于标准的Introduction层层递进的写作模式：大背景大帽子-->从替代燃料引入醇类燃料再引入正丁醇-->再引入正丁醇与氢气掺烧，提出如何降低NOx排放-->引入EGR降 …
a brief introduction后的介词到底是about还是of还是to啊？ - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区 …
如何仅从Introduction看出一篇文献的水平？ - 知乎
introduction大致对应 ’background on the field‘ 这一部分。 个人认为，取决于文章的目的，是填补了研究领域空白，还是更新了人们对某个现象的认知，或者精进了某种工具，做出了重大预测，不同的文 …
word choice - What do you call a note that gives preliminary ...
Feb 2, 2015 · A suitable word for your brief introduction is preamble. It's not as formal as preface, and can be as short as a sentence (which would be unusual for a preface). Preamble can be …
英文论文有具体的格式吗？ - 知乎
首先你要明白，Essay由introduction、body、conclusion、reference四部分组成。 1、字体设置 全文统一用T imes New Roman字体，小四，1.5倍行距。
论文里面introduction和overview有什么区别？ - 知乎
introduction实际上是一个帽子，告诉读者你为什么要做这个研究、写这篇文章。 其中包括了其他研究者在这个分支上的近期工作和你自己的创新点。 overview 经常被翻译成“概述”，是对一个分支内的状 …
毕业论文的绪论应该怎么写？ - 知乎
在Introduction结尾时，需注意研究目的完全可以作为Introduction的结尾，也可以简单介绍一下文章的结构及每一部分的主要内容，从而起到画龙点睛的作用，使读者了解文章的轮廓和脉络。 总结下SCI …
怎样写好英文论文的 Introduction 部分呢？ - 知乎
Introduction应该是一篇论文中最难写的一部分，也是最重要的。“A good introduction will “sell” the study to editors, reviewers, readers, and sometimes even the media.” [1]。通过Introduction可以判断一篇论文的好坏，因此我 …
怎样写好英文论文的 Introduction 部分？ - 知乎
Why An Introduction Is Needed？ 「从文章的大结构来看Introduction提出了你的研究问题，这个问题的答案应该在文章的Discussion或者Conclusion部分呈现给读者，也就是在文章的首尾形成一个前后呼应的关系」。 那Introduction引言 …
Difference between "introduction to" and "introduction of"
May 22, 2011 · Here, "Introduction of" refers to bringing something into a place or situation. "Can you give me an introduction to the president of the company?" "Introduction to" is more commonly used in referring to …
科学引文索引（SCI）论文的引言（Introduction）怎么写？ - 知乎
Introduction一共分为8段，属于标准的Introduction层层递进的写作模式：大背景大帽子-->从替代燃料引入醇类燃料再引入正丁醇-->再引入正丁醇与氢气掺烧，提出如何降低NOx排放-->引入EGR降低NOx排放-->提出存在问题并明确本文研 …
a brief introduction后的介词到底是about还是of还是to啊？ - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区氛围、独特的产品机制以及结构化和易获得的优质内 …
