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Books in Statistics and probability

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101-110 of 233 results in All results

Frontiers of Pattern Recognition

  • 1st Edition
  • May 10, 2014
  • Satosi Watanabe
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 6 8 9 4 - 1
Frontiers of Pattern Recognition contains the proceedings of the International Conference on Frontiers of Pattern Recognition which took place on January 18-20, 1971, at the University of Hawaii, Honolulu. The compendium consists of 30 papers from authorities from eleven different countries, which describe the frontiers of pattern recognition as viewed from diverse viewpoints. Topics discussed include some techniques for recognizing structures in pictures, grammatical inference, syntactic pattern recognition and stochastic languages, and pattern cognition and the organization of information. Also covered are subjects on human face recognition, cluster analysis, and learning algorithms of pattern recognition in non-stationary conditions. Computer scientists, mathematicians, statisticians, linguists, and psychologists will find the book informative.

Introductory Statistics for the Behavioral Sciences

  • 1st Edition
  • May 10, 2014
  • Joan Welkowitz + 2 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 5 8 1 5 - 7
Introductory Statistics for the Behavioral Sciences provides an introduction to statistical concepts and principles. This book emphasizes the robustness of parametric procedures wherein such significant tests as t and F yield accurate results even if such assumptions as equal population variances and normal population distributions are not well met. Organized into three parts encompassing 16 chapters, this book begins with an overview of the rationale upon which much of behavioral science research is based, namely, drawing inferences about a population based on data obtained from a sample. This text then examines the primary goal of descriptive statistics to bring order out of chaos. Other chapters consider the concept of variability and its applications. This book discusses as well the essential characteristics of a group of scores. The final chapter deals with the chi-square analysis. This book is a valuable resource for students of statistics as well as for undergraduates majoring in psychology, sociology, and education.

Applied Stochastic Processes

  • 1st Edition
  • May 9, 2014
  • G. Adomian
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 5 9 0 8 - 6
Applied Stochastic Processes is a collection of papers dealing with stochastic processes, stochastic equations, and their applications in many fields of science. One paper discusses stochastic systems involving randomness in the system itself that can be a large dynamical multi-input, multi-output system. Examples of a large system are the national economy of a major country or when an acoustic wave is propagating as in the atmosphere, ocean, or sea. Another paper proves that only the average properties of the molecules of biology can be measured with precision in the test tube; and disputes a "simplistic" model of the cell as defined by a miniature Laplaces' universe. The paper notes that the way existing cells are constructed implies that quantum mechanical principles lead to certain questions (about simple experiments) having only statistical answers. Another paper addresses the detection of distributed, fluctuating targets in a reverberation limited, randomly time, and space varying transmission media. This approach is done by using the concepts of "random Green's functions" and the "stochastic Green's function." The collection will prove useful for cellular researchers, mathematicians, physicist, engineers, and academicians in the field of applied mathematics, statistics, and chemistry.

Statistical Analysis

  • 1st Edition
  • May 9, 2014
  • A. A. Afifi + 1 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 6 0 7 1 - 6
Statistical Analysis: A Computer Oriented Approach discusses the probabilistic foundations of statistics, the standard statistical inference procedures, regression, and correlation analysis. The book also explains the analysis of variance and multivariate analysis, with an emphasis on the applications and interpretations of statistical tools. The text defines computer terminologies, coding sheets, format statements, and packaged statistical programs or software. Software and other related programs are tools for data analysis: the "frequency count program" analyzes discrete observations; and the "descriptive program" investigates one continuous variable. Other similar tools are the "descriptive program with strata" that evaluates more than one continuous random variable, and the "crosstabulation program" that reviews contingency tables. The book also explains the general linear model which is applied to the estimators and tests of hypotheses for simple and multiple linear regression models. The text shows how different packaged computer programs can be used to perform analyses of variance. For example, the factorial programs can analyze special designs of randomized blocks, replicated randomized blocks, and nested designs. For other special designs, including the split plot and Latin square designs, the investigator can make adaptations to the standard factorial program. The book is intended for students of statistical inference, computer programming, and readers interested in advanced mathematics.

An Introduction to Measure-Theoretic Probability

  • 2nd Edition
  • March 19, 2014
  • George G. Roussas
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 0 0 0 4 2 - 7
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 0 2 9 0 - 2
An Introduction to Measure-Theoretic Probability, Second Edition, employs a classical approach to teaching the basics of measure theoretic probability. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools that a student working toward an advanced degree in statistics, probability and other related areas should be equipped with. This edition requires no prior knowledge of measure theory, covers all its topics in great detail, and includes one chapter on the basics of ergodic theory and one chapter on two cases of statistical estimation. Topics range from the basic properties of a measure to modes of convergence of a sequence of random variables and their relationships; the integral of a random variable and its basic properties; standard convergence theorems; standard moment and probability inequalities; the Hahn-Jordan Decomposition Theorem; the Lebesgue Decomposition T; conditional expectation and conditional probability; theory of characteristic functions; sequences of independent random variables; and ergodic theory. There is a considerable bend toward the way probability is actually used in statistical research, finance, and other academic and nonacademic applied pursuits. Extensive exercises and practical examples are included, and all proofs are presented in full detail. Complete and detailed solutions to all exercises are available to the instructors on the book companion site. This text will be a valuable resource for graduate students primarily in statistics, mathematics, electrical and computer engineering or other information sciences, as well as for those in mathematical economics/finance in the departments of economics.

Effective Dynamics of Stochastic Partial Differential Equations

  • 1st Edition
  • February 27, 2014
  • Jinqiao Duan + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 0 0 8 8 2 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 2 6 9 - 7
Effective Dynamics of Stochastic Partial Differential Equations focuses on stochastic partial differential equations with slow and fast time scales, or large and small spatial scales. The authors have developed basic techniques, such as averaging, slow manifolds, and homogenization, to extract effective dynamics from these stochastic partial differential equations. The authors’ experience both as researchers and teachers enable them to convert current research on extracting effective dynamics of stochastic partial differential equations into concise and comprehensive chapters. The book helps readers by providing an accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations. Each chapter also includes exercises and problems to enhance comprehension.

Introduction to Probability Models

  • 11th Edition
  • January 8, 2014
  • Sheldon M. Ross
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 8 1 2 1 - 5
Introduction to Probability Models, Eleventh Edition is the latest version of Sheldon Ross's classic bestseller, used extensively by professionals and as the primary text for a first undergraduate course in applied probability. The book introduces the reader to elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research. The hallmark features of this text have been retained in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics. The 65% new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data. The book contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams. It also presents new applications of probability models in biology and new material on Point Processes, including the Hawkes process. There is a list of commonly used notations and equations, along with an instructor's solutions manual. This text will be a helpful resource for professionals and students in actuarial science, engineering, operations research, and other fields in applied probability.

Introduction to Probability

  • 2nd Edition
  • November 27, 2013
  • George G. Roussas
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 0 0 0 4 1 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 0 1 9 8 - 1
Introduction to Probability, Second Edition, discusses probability theory in a mathematically rigorous, yet accessible way. This one-semester basic probability textbook explains important concepts of probability while providing useful exercises and examples of real world applications for students to consider. This edition demonstrates the applicability of probability to many human activities with examples and illustrations. After introducing fundamental probability concepts, the book proceeds to topics including conditional probability and independence; numerical characteristics of a random variable; special distributions; joint probability density function of two random variables and related quantities; joint moment generating function, covariance and correlation coefficient of two random variables; transformation of random variables; the Weak Law of Large Numbers; the Central Limit Theorem; and statistical inference. Each section provides relevant proofs, followed by exercises and useful hints. Answers to even-numbered exercises are given and detailed answers to all exercises are available to instructors on the book companion site. This book will be of interest to upper level undergraduate students and graduate level students in statistics, mathematics, engineering, computer science, operations research, actuarial science, biological sciences, economics, physics, and some of the social sciences.

Life Table Techniques and Their Applications

  • 1st Edition
  • October 22, 2013
  • Krishnan Namboodiri + 1 more
  • H. H. Winsborough
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 8 8 8 8 - 8
This is the first volume to present a comprehensive treatment of the theory and application of life table techniques. The emphasis is placed on applications, and the theory is presented in such a way that individuals with minimal knowledge of calculus and matrix algebra can follow the argument.

Probabilistic Approach to Mechanisms

  • 1st Edition
  • Volume 8
  • October 22, 2013
  • B.Z. Sandler
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 8 9 8 6 - 1
This book discusses the application of probabilistics to the investigation of mechanical systems. The book shows, for example, how random function theory can be applied directly to the investigation of random processes in the deflection of cam profiles, pitch or gear teeth, pressure in pipes, etc. The author also deals with some other technical applications of probabilistic theory, including, amongst others, those relating to pneumatic and hydraulic mechanisms and roller bearings. Many of the aspects are illustrated by examples of applications of the techniques under discussion.

Related subjects

Probability theory and stochastic processes

Statistics