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Elsevier

Books in Statistics and probability

Exploring the fundamentals and advanced techniques of statistical analysis and probabilistic modeling, this selection supports data scientists, researchers, and decision-makers. It features cutting-edge methods, applications in industry, and case studies addressing uncertainty, risk assessment, and data-driven decision-making. These resources foster accurate interpretation, predictive analytics, and evidence-based insights essential for innovation in research, healthcare, finance, and policy development.

  • Introduction to Biostatistics

    A Guide to Design, Analysis and Discovery.
    • 1st Edition
    • Ronald N. Forthofer + 1 more
    • English
    The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. The book assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required.Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching.

  • Optimization Techniques in Statistics

    • 1st Edition
    • Jagdish S. Rustagi
    • English
    Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including annealing methods. The text features numerous applications, including:Finding maximum likelihood estimatesMarkov decision processesProgramming methods used to optimize monitoring of patients in hospitalsDerivation of the Neyman-Pearson lemmaThe search for optimal designsSimulation of a steel millSuitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics.

  • Operational Gaming

    An International Approach
    • 1st Edition
    • Ingolf StĂĄhl
    • English
    Operational Gaming: An International Approach is the result of research carried out at the International Institute for Applied Systems Analysis (IIASA) situated at Laxenburg (near Vienna), Austria, which relates game theory and system analysis to decision making. The book first shows the relationship of game theory, experimental gaming, and operational gaming through a state-of-the-art survey. This topic includes the history, context, type, and uses of gaming. Then, the text shifts to the discussion on operational gaming, including the definitions of institutional model and game situation concepts. An overview of gaming in different nations including USSR is provided. The book also studies the international transfer of games and the East-West international trade games. The future of this field of study, as well as its implications for humans, is also examined in the latter parts. This book will be of significance to those interested in game theories and those people involved in policy and decision making in their country or organization.

  • Contributions to Statistics

    • 1st Edition
    • P. C. Mahalanobis
    • C. R. Rao
    • English
    Contributions to Statistics focuses on the processes, methodologies, and approaches involved in statistics. The book is presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday. The selection first offers information on the recovery of ancillary information and combinatorial properties of partially balanced designs and association schemes. Discussions focus on combinatorial applications of the algebra of association matrices, sample size analogy, association matrices and the algebra of association schemes, and conceptual statistical experiments. The book then examines lattice sampling by means of Lahiri's sampling scheme; contributions of interpenetrating networks of samples; and apparently unconnected problems encountered in sampling work. The publication takes a look at screening processes, place of the design of experiments in the logic of scientific inference, and rarefaction. Topics include mathematical probability, scientific experience, combinatorial progress, gains and losses, criterion and scores, simple drug screening process, and screening of crop varieties. The manuscript then reviews the estimation and interpretation of gross differences and the simple response variance; partially balanced asymmetrical factorial designs; and approximation of distributions of sums of independent summands by infinitely divisible distributions. The selection is a dependable reference for statisticians and researchers interested in the processes, methodologies, and approaches employed in statistics.

  • An Introduction to Probability and Mathematical Statistics

    • 1st Edition
    • Howard G. Tucker
    • Ralph P. Boas
    • English
    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.

  • Theory of Markov Processes

    • 1st Edition
    • E. B. Dynkin
    • T. Köváry
    • English
    Theory of Markov Processes provides information pertinent to the logical foundations of the theory of Markov random processes. This book discusses the properties of the trajectories of Markov processes and their infinitesimal operators. Organized into six chapters, this book begins with an overview of the necessary concepts and theorems from measure theory. This text then provides a general definition of Markov process and investigates the operations that make possible an inspection of the class of Markov processes corresponding to a given transition function. Other chapters consider the more complicated operation of generating a subprocess. This book discusses as well the construction of Markov processes with given transition functions. The final chapter deals with the conditions to be imposed on the transition function so that among the Markov processes corresponding to this function, there should be at least one. This book is a valuable resource for mathematicians, students, and research workers.

  • Introductory Statistics for the Behavioral Sciences

    • 1st Edition
    • Joan Welkowitz + 2 more
    • English
    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.

  • Stochastic Modelling of Social Processes

    • 1st Edition
    • Andreas Diekmann + 1 more
    • English
    Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.

  • Crime, the Police and Criminal Statistics

    An Analysis of Official Statistics for England and Wales Using Econometric Methods
    • 1st Edition
    • R. A. Carr-Hill + 1 more
    • Peter H. Rossi
    • English
    Crime, The Police and Criminal Statistics: An Analysis of Official Statistics for England and Wales Using Econometric Methods presents a study of the relation between official criminal statistics and the activities which they are supposed to reflect. The book is comprised of three sections: the theoretical background, the empirical argument, and certain implications of the study. The first section discusses the criminological, sociological, and economic theories under consideration in the light of available evidence, and their relevance to the countries and period of the study: England and Wales in the 1960s. The second section describes the techniques employed and the interpretations of the obtained results. The final section considers the examination of the use of official criminal statistics in discussions of policy; and the review of models of suitable or optimum strategies of punishment and deterrence. The monograph will be of interest to criminologists, economists, sociologists, and statisticians.

  • Contributions to Survey Sampling and Applied Statistics

    Papers in Honor of H.O Hartley
    • 1st Edition
    • H. O. Hartley
    • H. A. David
    • English
    Contributions to Survey Sampling and Applied Statistics: Papers in Honor of H. O. Hartley covers the significant advances in survey sampling, modeling, and applied statistics. This book is organized into five parts encompassing 20 chapters. The opening part looks into some aspects of statistics, sampling, randomization, predictive estimation, and internal congruency. This part also considers the properties of variance estimation for a specified multiple frame survey design and some sampling designs involving unequal probabilities of selection and robust estimation of a finite population total. The next parts present the analysis and the theoretical and practical aspects of linear models, as well as the applications of time series analysis. These topics are followed by discussions of the testing for outliers in linear regression; the robustness of location estimators; and completeness comparisons among sample sequences. The closing part deals with the properties of norm estimators in regression and geometric programming. This part also provides tables of the normal conditioned on t-distribution. This book will prove useful to mathematicians and statisticians.

  • Stochastic Analysis

    Liber Amicorum for Moshe Zakai
    • 1st Edition
    • Eddy Mayer-Wolf + 2 more
    • English
    Stochastic Analysis: Liber Amicorum for Moshe Zakai focuses on stochastic differential equations, nonlinear filtering, two-parameter martingales, Wiener space analysis, and related topics. The selection first ponders on conformally invariant and reflection positive random fields in two dimensions; real time architectures for the Zakai equation and applications; and quadratic approximation by linear systems controlled from partial observations. Discussions focus on predicted miss, review of basic sequential detection problems, multigrid algorithms for the Zakai equation, invariant test functions and regularity, and reflection positivity. The text then takes a look at a model of stochastic differential equation in Hubert spaces applicable to Navier Stokes equation in dimension 2; wavelets as attractors of random dynamical systems; and Markov properties for certain random fields. The publication examines the anatomy of a low-noise jump filter, nonlinear filtering with small observation noise, and closed form characteristic functions for certain random variables related to Brownian motion. Topics include derivation of characteristic functions for the examples, proof of the theorem, sequential quadratic variation test, asymptotic optimal filters, mean decision time, and asymptotic optimal filters. The selection is a valuable reference for researchers interested in stochastic analysis.

  • Frontiers of Pattern Recognition

    The Proceedings of the International Conference on Frontiers of Pattern Recognition
    • 1st Edition
    • Satosi Watanabe
    • English
    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.

  • Graphical Representation of Multivariate Data

    • 1st Edition
    • Peter C. C. Wang
    • English
    Graphical Representation of Multivariate Data is a collection of papers that explores and expands the use of graphical methods to represent multivariate data. One paper explains the application of the graphical representation of k-dimensional data technique as a statistical tool to analyze Soviet foreign policy. The technique encompasses data files, data modifications, and transformations of Soviet foreign policy in 25 countries from 1964 to 1975. The Faces methodology (a representation of multidimensional data developed by Herman Chernoff) analyzes ten sets of these data. Another paper describes the Faces techniques, Andrew's sine curves, Anderson's metroglyphs, which are then compared to Facial representations. Examples show the application of Chernoff Faces at the Los Alamos Scientific Laboratory. The paper considers the technique's main drawback—subjectivit... a positive feature that can be overcome. Another paper agrees that computer-generated faces are a good representations to induce actions on tasks based on multivariate metrical data, The paper also acknowledges that the stereotyping of faces can be useful when making a display. One paper investigates the responsiveness to facial and verbal cues using the Syracuse person perception tool as a measuring tool. The collection is suitable for investigators, professors, or students in mathematics, computer science, or engineering courses. It will also be very helpful for researchers involved in graphical display of multivariate data from a wide range of different fields such as statistics, economics, regional planning, clinical research, social/political science, psychiatric studies, international relations, international trade, and arms transfer.

  • Scientific Inference, Data Analysis, and Robustness

    Proceedings of a Conference Conducted by the Mathematics Research Center, the University of Wisconsin—Madison, November 4–6, 1981
    • 1st Edition
    • G. E. P. Box + 2 more
    • English
    Mathematics Research Center Symposium: Scientific Inference, Data Analysis, and Robustness focuses on the philosophy of statistical modeling, including model robust inference and analysis of data sets. The selection first elaborates on pivotal inference and the conditional view of robustness and some philosophies of inference and modeling, including ideas on modeling, significance testing, and scientific discovery. The book then ponders on parametric empirical Bayes confidence intervals, ecumenism in statistics, and frequency properties of Bayes rules. Discussions focus on consistency of Bayes rules, scientific method and the human brain, and statistical estimation and criticism. The book takes a look at the purposes and limitations of data analysis, likelihood, shape, and adaptive inference, statistical inference and measurement of entropy, and the robustness of a hierarchical model for multinomials and contingency tables. Topics include numerical results for contingency tables and robustness, multinomials, flattening constants, and mixed Dirichlet priors, entropy and likelihood, and test as measurement of entropy. The selection is a valuable reference for researchers interested in robust inference and analysis of data sets.

  • Classification and Clustering

    Proceedings of an Advanced Seminar Conducted by the Mathematics Research Center, the University of Wisconsin at Madison, May 3–5, 1976
    • 1st Edition
    • J. Van Ryzin
    • English
    Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.

  • Statistical Analysis

    A Computer Oriented Approach
    • 1st Edition
    • A. A. Afifi + 1 more
    • English
    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.

  • Applied Stochastic Processes

    • 1st Edition
    • G. Adomian
    • English
    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.

  • An Introduction to Measure-Theoretic Probability

    • 2nd Edition
    • George G. Roussas
    • English
    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
    • Jinqiao Duan + 1 more
    • English
    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
    • Sheldon M. Ross
    • English
    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
    • George G. Roussas
    • English
    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.

  • Evaluating Performance in Physical Education

    • 1st Edition
    • B. Don Franks + 1 more
    • English
    Evaluating Performance in Physical Education describes the tools and techniques that can be used by teachers to assess student performance, curriculum, and method of teaching. The book discusses conventional material in evaluating physical education performance through written, fitness tests, and elementary statistics. The text also explains nonparametric statistics, subjective evaluation, and a theoretical model for fitness and performance. The authors review the functions, evaluation, and administration of testing. The authors also explain in more detail subjective evaluation and offer three forms: 1) experience of the teacher; 2) skill to be rated; and 3) length of time for rating. In testing events, nonparametric statistical procedures show more reliability; parametric procedures are preferably to be used in established research stations. The authors also list some guidelines to be followed in evaluating the student such as objectives, assignment of grades, and acceptance of the grading plan. The book also discusses procedures when evaluation involves large groups. The text can assist physical education teachers, school administrators, and educators in evaluating their subject course or curricula.

  • Probabilistic Approach to Mechanisms

    • 1st Edition
    • Volume 8
    • B.Z. Sandler
    • English
    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.

  • Life Table Techniques and Their Applications

    • 1st Edition
    • Krishnan Namboodiri + 1 more
    • H. H. Winsborough
    • English
    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.

  • Structures and Stochastic Methods

    • 1st Edition
    • A.S. Cakmak
    • English
    Despite advances in the field of geotechnical earthquake engineering, earthquakes continue to cause loss of life and property in one part of the world or another. The Third International Conference on Soil Dynamics and Earthquake Engineering, Princeton University, Princeton, New Jersey, USA, 22nd to 24th June 1987, provided an opportunity for participants from all over the world to share their expertise to enhance the role of mechanics and other disciplines as they relate to earthquake engineering. The edited proceedings of the conference are published in four volumes. This volume covers: Structures, Dams, Retaining Walls and Slopes, Underground Structures, and Stochastic Methods. Together with its companion volumes, it is hoped that it will contribute to the further development of techniques, methods and innovative approaches in soil dynamics and earthquake engineering.

  • Laboratory Statistics

    Handbook of Formulas and Terms
    • 1st Edition
    • Anders Kallner
    • English
    Laboratory Statistics: Handbook of Formulas and Terms presents common strategies for comparing and evaluating numerical laboratory data. In particular, the text deals with the type of data and problems that laboratory scientists and students in analytical chemistry, clinical chemistry, epidemiology, and clinical research face on a daily basis. This book takes the mystery out of statistics and provides simple, hands-on instructions in the format of everyday formulas. As far as possible, spreadsheet shortcuts and functions are included, along with many simple worked examples. This book is a must-have guide to applied statistics in the lab that will result in improved experimental design and analysis.

  • Machine Learning: Theory and Applications

    • 1st Edition
    • Volume 31
    • English
    Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.

  • Chi-Squared Goodness of Fit Tests with Applications

    • 1st Edition
    • Narayanaswamy Balakrishnan + 2 more
    • English
    Chi-Squared Goodness of Fit Tests with Applications provides a thorough and complete context for the theoretical basis and implementation of Pearson’s monumental contribution and its wide applicability for chi-squared goodness of fit tests. The book is ideal for researchers and scientists conducting statistical analysis in processing of experimental data as well as to students and practitioners with a good mathematical background who use statistical methods. The historical context, especially Chapter 7, provides great insight into importance of this subject with an authoritative author team. This reference includes the most recent application developments in using these methods and models.

  • Analysis and Probability

    • 1st Edition
    • Aurel Spataru
    • English
    Probability theory is a rapidly expanding field and is used in many areas of science and technology. Beginning from a basis of abstract analysis, this mathematics book develops the knowledge needed for advanced students to develop a complex understanding of probability. The first part of the book systematically presents concepts and results from analysis before embarking on the study of probability theory. The initial section will also be useful for those interested in topology, measure theory, real analysis and functional analysis. The second part of the book presents the concepts, methodology and fundamental results of probability theory. Exercises are included throughout the text, not just at the end, to teach each concept fully as it is explained, including presentations of interesting extensions of the theory. The complete and detailed nature of the book makes it ideal as a reference book or for self-study in probability and related fields.

  • R and Data Mining

    Examples and Case Studies
    • 1st Edition
    • Yanchang Zhao
    • English
    R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis.

  • Statistics in Spectroscopy

    • 1st Edition
    • Howard Mark + 1 more
    • English
    This tutorial offers a basic hands-on approach to statistical analysis for chemists and spectroscopists. Without involving complicated mathematics, this book is designed to provide the reader with the basic principles underlying the use of common mathematical and statistical tools. Particular emphasis has been given to problem-solving applications and the proper use and interpretation of spectroscopic data. With exercises throughout, this book is also suitable for use as a textbook in analytical chemistry, instrumental analysis, and statistics in chemistry courses.

  • A Statistical Manual for Chemists

    • 2nd Edition
    • Edward Bauer
    • English
    A Statistical Manual for Chemists, Second Edition presents simple and fast statistical tools for data analysis of working chemists. This edition is organized into nine chapters and begins with an overview of the fundamental principles of the statistical techniques used in experimental data analysis. The subsequent chapters deal with the concept of statistical average, experimental design, and analysis of variance. The discussion then shifts to control charts, with particular emphasis on variable charts that are more useful to chemists and chemical engineers. A chapter focuses on the effect of correlated variables and their analysis using various tools. The concluding chapters deal with the theory and aspects of sampling and control of routine analysis. This edition is of great benefit to working chemists and chemical engineers.

  • Sample Size Methodology

    • 1st Edition
    • M. M. Desu
    • English
    One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropriate techniques for attacking the general question of sample size determination in problems of estimation, tests of hypotheses, selection, and clinical trial design are all presented, and will help the reader in formulating an appropriate problem of sample size and in obtaining the solution. The book can be used as a text in a senior-level or a graduate course on sample size methodology.

  • Stochastic Wave Propagation

    • 1st Edition
    • K. Sobczyk
    • English
    This is a concise, unified exposition of the existing methods of analysis of linear stochastic waves with particular reference to the most recent results. Both scalar and vector waves are considered. Principal attention is concentrated on wave propagation in stochastic media and wave scattering at stochastic surfaces. However, discussion extends also to various mathematical aspects of stochastic wave equations and problems of modelling stochastic media.

  • Simulation

    • 5th Edition
    • Sheldon M. Ross
    • English
    The 5th edition of Ross’s Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This latest edition features all-new material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis. Additionally, the 5th edition expands on Markov chain monte carlo methods, and offers unique information on the alias method for generating discrete random variables. By explaining how a computer can be used to generate random numbers and how to use these random numbers to generate the behavior of a stochastic model over time, Ross’s Simulation, 5th edition presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model.

  • Identifiability In Stochastic Models

    • 1st Edition
    • B. L. S. Prakasa Rao
    • English
    The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of "characterization problems" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.

  • Bioinformatics in Human Health and Heredity

    • 1st Edition
    • Volume 28
    • English
    The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics, a series of self-contained reference books. Each volume is devoted to a particular topic in statistics with Volume 28 dealing with bioinformatics. Every chapter is written by prominent workers in the area to which the volume is devoted. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriente... techniques, with the applied statistician in mind as the primary audience.

  • Statistics in Medicine

    • 3rd Edition
    • Robert H. Riffenburgh
    • English
    Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan studies from conception to publication and what to do with your data, and follows with step-by-step instructions for biostatistical methods from the simplest levels (averages, bar charts) progressively to the more sophisticated methods now being seen in medical articles (multiple regression, noninferiority testing). Examples are given from almost every medical specialty and from dentistry, nursing, pharmacy, and health care management. A preliminary guide is given to tailor sections of the text to various lengths of biostatistical courses.

  • Time Series Analysis: Methods and Applications

    • 1st Edition
    • Volume 30
    • English
    The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriente... techniques, with the applied statistician in mind as the primary audience.

  • Statistics for Physical Sciences

    An Introduction
    • 1st Edition
    • Brian Martin
    • English
    Statistics for Physical Sciences is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origins. It steers a path between the extremes of a recipe of methods with a collection of useful formulas, and a full mathematical account of statistics, while at the same time developing the subject in a logical way. The book can be read in its entirety by anyone with a basic exposure to mathematics at the level of a first-year undergraduate student of physical science and should be useful for practising physical scientists, plus undergraduate and postgraduate students in these fields.

  • Probability and Random Processes

    With Applications to Signal Processing and Communications
    • 2nd Edition
    • Scott Miller + 1 more
    • English
    Probability and Random Processes, Second Edition presents pertinent applications to signal processing and communications, two areas of key interest to students and professionals in today's booming communications industry. The book includes unique chapters on narrowband random processes and simulation techniques. It also describes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and others. Exceptional exposition and numerous worked out problems make this book extremely readable and accessible. The authors connect the applications discussed in class to the textbook. The new edition contains more real world signal processing and communications applications. It introduces the reader to the basics of probability theory and explores topics ranging from random variables, distributions and density functions to operations on a single random variable. There are also discussions on pairs of random variables; multiple random variables; random sequences and series; random processes in linear systems; Markov processes; and power spectral density. This book is intended for practicing engineers and students in graduate-level courses in the topic.

  • Statistical Aspects of Water Quality Monitoring

    • 1st Edition
    • Volume 27
    • A.H. El-Shaarawi + 1 more
    • English
    This volume contains selected papers from the ``Workshop on the Statistical Aspects of Water Quality Monitoring'', held on October 7-10 1985, at the National Water Research Institute in Burlington, Ontario, Canada. The prime objective of the Workshop was to generate interaction between the statistical community and scientists working in the area of Water Quality Monitoring. To this end, topics covered in this Workshop fall into two categories: (1) Methods Development, and (2) the Imaginative Application of Existing Methodologies. Subjects covered include: Time Series, Estimation of Loading, Clustering, Model Development, Censoring Data Analysis, Quality Control and Data Acquisition.In the area of environmental sciences, statistical applications are still in their infancy, with few attempts to systematically develop techniques dealing with environmental issues. The publication of this book is one step towards identifying appropriate statistical techniques and diagnosing problems in Water Quality Monitoring which require new statistical methodologies. The papers presented in this volume represent international expertise, consolidating detailed information on both conventional and new methods.

  • Stochastic Control by Functional Analysis Methods

    • 1st Edition
    • Volume 11
    • A. Bensoussan
    • English

  • Applications of Variational Inequalities in Stochastic Control

    • 1st Edition
    • Volume 12
    • A. Bensoussan + 1 more
    • English

  • Probabilities and Potential, B

    Theory of Martingales
    • 1st Edition
    • Volume 72
    • C. Dellacherie + 1 more
    • English

  • Statistical Methods in the Atmospheric Sciences

    • 3rd Edition
    • Volume 100
    • Daniel S. Wilks
    • English
    Statistical Methods in the Atmospheric Sciences, Third Edition, explains the latest statistical methods used to describe, analyze, test, and forecast atmospheric data. This revised and expanded text is intended to help students understand and communicate what their data sets have to say, or to make sense of the scientific literature in meteorology, climatology, and related disciplines. In this new edition, what was a single chapter on multivariate statistics has been expanded to a full six chapters on this important topic. Other chapters have also been revised and cover exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, and time series analysis. There is now an expanded treatment of resampling tests and key analysis techniques, an updated discussion on ensemble forecasting, and a detailed chapter on forecast verification. In addition, the book includes new sections on maximum likelihood and on statistical simulation and contains current references to original research. Students will benefit from pedagogical features including worked examples, end-of-chapter exercises with separate solutions, and numerous illustrations and equations. This book will be of interest to researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines.

  • Practical Business Statistics, Instructor Solutions Manual (e-only)

    • 1st Edition
    • Andrew F. Siegel
    • English
    Practical Business Statistics is a conceptual and definitive guide to managerial statistics that masterfully maintains mathematical correctness. The book aims to help users learn to analyze and process data with uncertainty, while encouraging readers to use practical computer applications. The book is divided into 18 chapters, all of which follow a uniform presentation outline: starting with an overview that explains why the subject matter is important to business and concluding with a comprehensive summary, with keywords, questions, problems, database exercises and projects. The book features the following concepts of business statistics: o The role of statistics in business o Classification of data sets o Interpretation of typical values and percentiles o Variability and probability o Working with uncertain numbers o Random sampling o Confidence intervals o Hypothesis testing o Correlation and regression o Time series o ANOVA o Ordinal data and non-normal distributions o Chi-square and managing variations The book presents information in a lively, user -friendly style, while maintaining technical accuracy. The text also features excellent examples with real-world data relating to the functional areas of business: finance, accounting, and marketing. Students in business and management statistics courses, quantitative methods in management, and analytics will find this book an excellent reference for learning. Business managers and lecturers will also find this book invaluable.

  • An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

    • 1st Edition
    • Mark Pinsky + 1 more
    • English

  • Exploring Monte Carlo Methods

    • 1st Edition
    • William L. Dunn + 1 more
    • English
    Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon’s needle problem" provides a unifying theme as it is repeatedly used to illustrate many features of Monte Carlo methods. This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners.

  • Observation Oriented Modeling

    Analysis of Cause in the Behavioral Sciences
    • 1st Edition
    • James W. Grice
    • English
    This book introduces a new data analysis technique that addresses long standing criticisms of the current standard statistics. Observation Oriented Modelling presents the mathematics and techniques underlying the new method, discussing causality, modelling, and logical hypothesis testing. Examples of how to approach and interpret data using OOM are presented throughout the book, including analysis of several classic studies in psychology. These analyses are conducted using comprehensive software for the Windows operating system.

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