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Mathematical Methods of Statistics
Author: Harald Cramér
Publisher: Princeton University Press
Published: 1999-04-12
Total Pages: 596
ISBN-13: 9780691005478
DOWNLOAD EBOOK →In this classic of statistical mathematical theory, Harald Cram r 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 Cram r'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.
Mathematical Methods in Statistics
Author: David Freedman
Publisher: W W Norton & Company Incorporated
Published: 1981
Total Pages: 0
ISBN-13: 9780393952230
DOWNLOAD EBOOK →Methods of Mathematics Applied to Calculus, Probability, and Statistics
Author: Richard W. Hamming
Publisher: Courier Corporation
Published: 2012-06-28
Total Pages: 882
ISBN-13: 0486138879
DOWNLOAD EBOOK →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.
Mathematical Statistics
Author: Dieter Rasch
Publisher: John Wiley & Sons
Published: 2018-01-09
Total Pages: 886
ISBN-13: 1119385237
DOWNLOAD EBOOK →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.
Mathematical Methods of Statistics (PMS-9), Volume 9
Author: Harald Cramér
Publisher: Princeton University Press
Published: 2016-06-02
Total Pages: 593
ISBN-13: 1400883865
DOWNLOAD EBOOK →Harald Cramér’s classic synthesis of statistical mathematical theory—an invaluable resource for students and practitioners alike In the 1930s, as 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. In this incisive and authoritative book, Harald Cramér unites these two major lines of development, providing a masterly exposition of the mathematical methods of modern statistics that set the standard in the field still followed today. Requiring only a working knowledge of undergraduate mathematics, this self-contained book begins with an introduction to the fundamental concept of a distribution and of integration with respect to a distribution. It goes on to discuss the general theory of random variables and probability distributions, the theory of sampling, statistical estimation, and tests of significance. Blending lucid and accessible writing with mathematical rigor, Mathematical Methods of Statistics belongs on the shelf of anyone interested in statistical methods and remains the standard reference on the subject today.
Mathematical Statistics
Author: George R. Terrell
Publisher: Springer Science & Business Media
Published: 2006-04-06
Total Pages: 467
ISBN-13: 0387227695
DOWNLOAD EBOOK →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.
Mathematical and Statistical Models and Methods in Reliability
Author: V.V. Rykov
Publisher: Springer Science & Business Media
Published: 2010-11-02
Total Pages: 465
ISBN-13: 0817649719
DOWNLOAD EBOOK →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.
Data Science and Machine Learning
Author: Dirk P. Kroese
Publisher: CRC Press
Published: 2019-11-20
Total Pages: 538
ISBN-13: 1000730778
DOWNLOAD EBOOK →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
Mathematical and Statistical Methods for Genetic Analysis
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 376
ISBN-13: 0387217509
DOWNLOAD EBOOK →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.
