Download or read book Mathematical Methods of Statistics written by Harald Cramér and published by . This book was released on 1946 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Methods of Statistics written by Harald Cramér and published by Princeton University Press. This book was released on 1999-04-12 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this classic of statistical mathematical theory, Harald Cramér joins the two major lines of development in the field: while British and American statisticians were developing the science of statistical inference, French and Russian probabilitists transformed the classical calculus of probability into a rigorous and pure mathematical theory. The result of Cramér's work is a masterly exposition of the mathematical methods of modern statistics that set the standard that others have since sought to follow. For anyone with a working knowledge of undergraduate mathematics the book is self contained. The first part is an introduction to the fundamental concept of a distribution and of integration with respect to a distribution. The second part contains the general theory of random variables and probability distributions while the third is devoted to the theory of sampling, statistical estimation, and tests of significance.
Download or read book Mathematical Methods in Statistics written by David Freedman and published by W W Norton & Company Incorporated. This book was released on 1981 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Methods of Mathematics Applied to Calculus Probability and Statistics written by Richard W. Hamming and published by Courier Corporation. This book was released on 2012-06-28 with total page 882 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 4-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. 1985 edition. Includes 310 figures and 18 tables.
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 846 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.
Download or read book Mathematical Methods of Reliability Theory written by B. V. Gnedenko and published by Academic Press. This book was released on 2014-06-20 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Methods of Reliability Theory discusses fundamental concepts of probability theory, mathematical statistics, and an exposition of the relationships among the fundamental quantitative characteristics encountered in the theory. The book deals with the set-theoretic approach to reliability theory and the central concepts of set theory to the phenomena. It also presents methods of finding estimates for reliability parameters based on observations and methods of testing reliability hypotheses. Based on mathematical statistics, the book also explains formulation of some selected results. It presents a method that increases the reliability of manufactured articles—redundancy. An important part of product quality control is the standards of acceptance-sampling plans which require simplicity, wide content for flexibility, comprehensive characteristics, and variability. The book also tackles economical and rational methods of sampling inspections, highlighting the need for a correct evaluation of environmental conditions—the factors which predetermine the choice of the inspection method. The book then explains how to estimate the efficiency of the operation of the sampling plan after its selection. The book can be helpful for engineers, mathematicians, economists, or industrial managers, as well as for other professionals who work in the technological, political, research, structural, and physico-chemical areas.
Download or read book Mathematical Methods In Sample Surveys written by Howard G Tucker and published by World Scientific. This book was released on 1998-10-15 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about both the mathematics of sample surveys and about sample surveys. The mathematics is both elementary and rigorous. It is suitable for a one year junior-senior level course for mathematics and statistics majors as well as for students in the social sciences who are not handicapped by a fear of proofs in mathematics. It requires no previous knowledge of statistics, and it could actually serve as an introduction to statistics. A sizeable part of the book covers the discrete probability needed for the sampling methods covered. Topics then covered are: simple random sampling, sampling with unequal probabilities, linear relationships, stratified sampling, cluster sampling and two-stage sampling.
Download or read book Mathematical and Statistical Models and Methods in Reliability written by V.V. Rykov and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Download or read book Mathematical Statistics written by George R. Terrell and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces the mathematical concepts and methods that underlie statistics. The course is unified, in the sense that no prior knowledge of probability theory is assumed, being developed as needed. The book is committed to both a high level of mathematical seriousness and to an intimate connection with application. In its teaching style, the book is * mathematically complete * concrete * constructive * active. The text is aimed at the upper undergraduate or the beginning Masters program level. It assumes the usual two-year college mathematics sequence, including an introduction to multiple integrals, matrix algebra, and infinite series.
Download or read book Mathematical and Statistical Methods in Reliability written by Bo Lindqvist and published by World Scientific. This book was released on 2003 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains extended versions of carefully selected and reviewed papers presented at the Third International Conference on Mathematical Methods in Reliability, held in Norway in 2002. It provides an overview of current research activities in reliability theory. The authors are all leading experts in the field. Readership: Graduate students, academics and professionals in probability & statistics, reliability analysis, survival analysis, industrial engineering, software engineering, operations research and applied mathematics research.
Download or read book Mathematical Statistics written by Johann Pfanzagl and published by Springer. This book was released on 2017-10-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed description of the development of statistical theory. In the mid twentieth century, the development of mathematical statistics underwent an enduring change, due to the advent of more refined mathematical tools. New concepts like sufficiency, superefficiency, adaptivity etc. motivated scholars to reflect upon the interpretation of mathematical concepts in terms of their real-world relevance. Questions concerning the optimality of estimators, for instance, had remained unanswered for decades, because a meaningful concept of optimality (based on the regularity of the estimators, the representation of their limit distribution and assertions about their concentration by means of Anderson’s Theorem) was not yet available. The rapidly developing asymptotic theory provided approximate answers to questions for which non-asymptotic theory had found no satisfying solutions. In four engaging essays, this book presents a detailed description of how the use of mathematical methods stimulated the development of a statistical theory. Primarily focused on methodology, questionable proofs and neglected questions of priority, the book offers an intriguing resource for researchers in theoretical statistics, and can also serve as a textbook for advanced courses in statisticc.
Download or read book Mathematical Statistics written by Keith Knight and published by CRC Press. This book was released on 1999-11-24 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mathematical and Statistical Methods for Genetic Analysis written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written to equip students in the mathematical siences to understand and model the epidemiological and experimental data encountered in genetics research. This second edition expands the original edition by over 100 pages and includes new material. Sprinkled throughout the chapters are many new problems.
Download or read book Mathematical Statistics with Resampling and R written by Laura M. Chihara and published by John Wiley & Sons. This book was released on 2018-09-17 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques. This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition: • Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations • Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm • Offers a new section on "Google Interview Questions" that illustrates statistical thinking • Provides a new chapter on ANOVA • Contains more exercises and updated case studies, data sets, and R code Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.
Download or read book Precision written by C. X. Wong and published by Outskirts Press. This book was released on 2011-03 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Precision ... Statistical and Mathematical Methods in Horse Racing" thoroughly discusses the mathematical and statistical methods in handicapping and betting techniques. Differentiations, combinatorics, normal distribution, kernel smoothing and other mathematical and statistical tools are introduced. The jargons and equations are kept to a minimum so that it is easy to understand for most readers. More than 20 professional programs are freely available to download, which can allow readers to easily apply the methodology introduced in the book. This book can be divided into three main parts: horse handicapping (Chapters 2-6), wagering (Chapters 7-9) and theories in practices (Chapters 10-11). Chapter 1 will explain why long term gains are possible in horse racing. About horse handicapping, we will start with analysing racing forms in Chapter 2. Other handicapping factors such as weight carried, jockeys, trainers and pedigrees will be discussed in Chapter 3. Some advanced statistical methods, such as chi-square test and kernel smoothing, will be introduced in Chapter 4 to further analyse those handicapping factors discussed in previous chapters. The following two chapters are about probability estimations. In Chapter 5, normal distribution and multinominal logistic regression are introduced in estimating winning probability of each race horse. In Chapter 6, we will talk about some methods in misconceptions in estimating placed probability. Two main concepts in wagering, Kelly criterion and hedging, will be discussed in Chapters 7 and 8. To hit exotic pools, those theories in combinatorics in Chapter 9 will definitely help the readers. The author will share his experiences in betting syndicate in Chapter 10, and tell you how to be a successful professional horseplayer in the last Chapter. Some readers may find the mathematics in this book difficult, but the free program will take your pain away and do all the calculations. You can simply apply all the professional formulae by no more than a click, and pick your horses like an expert analyst. As an awardee in Asian-Pacific Mathematics Olympiad, the author abandoned his career as an actuary and became a key member in a gambling syndicate. This book was reprinted in the 4th edition in Hong Kong, ranked #2 in the best-selling chart in the international Chinese weekly Yazhou Zhoukan, and now available worldwide.
Download or read book Statistics for Mathematicians written by Victor M. Panaretos and published by Birkhäuser. This book was released on 2016-06-01 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
