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Elsevier

Books in Statistics

  • Semi-Markov Models

    Control of Restorable Systems with Latent Failures
    • 1st Edition
    • Yuriy E Obzherin + 1 more
    • English
    Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and utilizing the method of asymptotic phase enlargement developed by V.S. Korolyuk and A.F. Turbin. The work then explores semi-Markov models of latent failures control in two-component systems. Building on these results, solutions are provided for the problems of optimal periodicity of control execution. Finally, the book presents a comparative analysis of analytical and imitational modeling of some one- and two-component systems, before discussing practical applications of the results

  • Computational Statistics with R

    • 1st Edition
    • Volume 32
    • English
    R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered.

  • Doing Bayesian Data Analysis

    A Tutorial with R, JAGS, and Stan
    • 2nd Edition
    • John Kruschke
    • English
    Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business.

  • An Introduction to Probability and Statistical Inference

    • 2nd Edition
    • George G. Roussas
    • English
    An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual. This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture.

  • Mathematical Statistics with Applications in R

    • 2nd Edition
    • Kandethody M. Ramachandran + 1 more
    • English
    Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies.

  • Introduction to Probability and Statistics for Engineers and Scientists

    • 5th Edition
    • Sheldon M. Ross
    • English
    Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields.

  • Statistical Methods in Longitudinal Research

    Principles and Structuring Change
    • 1st Edition
    • Volume 1
    • Alexander von Eye
    • English
    These edited volumes present new statistical methods in a way that bridges the gap between theoretical and applied statistics. The volumes cover general problems and issues and more specific topics concerning the structuring of change, the analysis of time series, and the analysis of categorical longitudinal data. The book targets students of development and change in a variety of fields - psychology, sociology, anthropology, education, medicine, psychiatry, economics, behavioural sciences, developmental psychology, ecology, plant physiology, and biometry - with basic training in statistics and computing.

  • The Econometric Analysis of Non-Uniqueness in Rational Expectations Models

    • 1st Edition
    • Volume 201
    • L. Broze + 1 more
    • English
    This book is devoted to the econometric analysis of linear multivariate rational expectation models. It shows that the interpretation of multiplicity in terms of "new degrees of freedom" is consistent with a rigorous econometric reasoning. Non-uniqueness is the central theme of this book. Each chapter is concerned with a specific econometric aspect of rational expectations equilibria. The most constructive result lies in the possibility of an empirical determination of the equilibrium followed by the economy.

  • Systematic Glossary of the Terminology of Statistical Methods

    English/French/Spanish/Russian
    • 1st Edition
    • I. Paenson
    • English
    Systematic Glossary of the Terminology of Statistical Methods focuses on the elaboration of terms used in statistical methods. The publication first elaborates on the subject and basic methods of statistics, collection of statistical data, and classification and tabulation of statistical data. Discussions focus on the basic methods of statistics, units used in statistics, statistical inquiry, and the subject of statistics. The text then ponders on graphic presentation, averages, and measurements of variation. The manuscript examines essential theoretical distributions, moments of a frequency distribution, and statistical inference. Topics include point and interval estimations, binomial and normal distributions, nature of theoretical distributions, and elements of the theory of probability. The text also evaluates the theory of attributes, correlation, analysis of variance, and time series, including decomposition of time series, multiple correlation, and variance analysis with two or more principles of classification. The publication is a valuable reference for readers interested in the terms used in statistical methods.

  • Introduction to Structural Equation Models

    • 1st Edition
    • Otis Dudley Duncan
    • English
    Introduction to Structural Equation Models prepares the reader to understand the recent sociological literature on the use of structural equation models in research, and discusses methodological questions pertaining to such models. The material in first seven chapters is almost entirely standard, with the remaining four introducing progressively more open-ended issues, seducing the reader into beginning to think for himself about the properties of models or even to suggest problems that may intrigue the advanced student.

  • Statistical Inferences for Stochastic Processes

    Theory and Methods
    • 1st Edition
    • Ishwar V. Basawa + 1 more
    • English
    Statistical Inference Stochastic Processes provides information pertinent to the theory of stochastic processes. This book discusses stochastic models that are increasingly used in scientific research and describes some of their applications. Organized into three parts encompassing 12 chapters, this book begins with an overview of the basic concepts and procedures of statistical inference. This text then explains the inference problems for Galton–Watson process for discrete time and Markov-branching processes for continuous time. Other chapters consider problems of prediction, filtering, and parameter estimation for some simple discrete-time linear stochastic processes. This book discusses as well the ergodic type chains with finite and countable state-spaces and describes some results on birth and death processes that are of a non-ergodic type. The final chapter deals with inference procedures for stochastic processes through sequential procedures. This book is a valuable resource for graduate students.

  • Order Statistics & Inference

    Estimation Methods
    • 1st Edition
    • Narayanaswamy Balakrishnan + 1 more
    • English
    The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology... nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.

  • Fundamentals of Applied Probability and Random Processes

    • 2nd Edition
    • Oliver Ibe
    • English
    The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study.

  • Statistical Data Analysis and Inference

    • 1st Edition
    • Y. Dodge
    • English
    A wide range of topics and perspectives in the field of statistics are brought together in this volume. The contributions originate from invited papers presented at an international conference which was held in honour of C. Radhakrishna Rao, one of the most eminent statisticians of our time and a distinguished scientist.

  • Multivariate Analysis: Future Directions 2

    • 1st Edition
    • Volume 5
    • C.M. Cuadras + 1 more
    • English
    The contributions in this volume, made by distinguished statisticians in several frontier areas of research in multivariate analysis, cover a broad field and indicate future directions of research. The topics covered include discriminant analysis, multidimensional scaling, categorical data analysis, correspondence analysis and biplots, association analysis, latent variable models, bootstrap distributions, differential geometry applications and others. Most of the papers propose generalizations or new applications of multivariate analysis.This volume will be of great interest to statisticians, probabilists, data analysts and scientists working in the disciplines such as biology, biometry, ecology, medicine, econometry, psychometry and marketing. It will be a valuable guide to professors, researchers and graduate students seeking new and promising lines of statistical research.

  • Fundamentals of Statistics

    • 1st Edition
    • H. Mulholland + 1 more
    • English
    Fundamentals of Statistics covers topics on the introduction, fundamentals, and science of statistics. The book discusses the collection, organization and representation of numerical data; elementary probability; the binomial Poisson distributions; and the measures of central tendency. The text describes measures of dispersion for measuring the spread of a distribution; continuous distributions for measuring on a continuous scale; the properties and use of normal distribution; and tests involving the normal or student's ‘t’ distributions. The use of control charts for sample means; the ranges and fraction defective; the chi-squared distribution; the F distribution; and the bivariate distributions are also considered. The book deals with the idea of mathematical expectation and its relationship with mean, variance, and covariance, as well as weighted averages, death rates, and time series. Students studying for advanced level education or higher national certificates in Mechanical or Electrical Engineering, Mathematics, Chemistry, Biology, or Pharmacy, as well as university students taking such courses will find the book invaluable.

  • 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.

  • 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.

  • Operational Gaming

    An International Approach
    • 1st Edition
    • Ingolf Ståhl
    • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

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

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

  • 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.

  • 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.

  • Statistical Mechanics

    • 3rd Edition
    • Paul D. Beale
    • English
    Statistical Mechanics explores the physical properties of matter based on the dynamic behavior of its microscopic constituents. After a historical introduction, this book presents chapters about thermodynamics, ensemble theory, simple gases theory, Ideal Bose and Fermi systems, statistical mechanics of interacting systems, phase transitions, and computer simulations. This edition includes new topics such as BoseEinstein condensation and degenerate Fermi gas behavior in ultracold atomic gases and chemical equilibrium. It also explains the correlation functions and scattering; fluctuationdissipati... theorem and the dynamical structure factor; phase equilibrium and the Clausius-Clapeyron equation; and exact solutions of one-dimensional fluid models and two-dimensional Ising model on a finite lattice. New topics can be found in the appendices, including finite-size scaling behavior of Bose-Einstein condensates, a summary of thermodynamic assemblies and associated statistical ensembles, and pseudorandom number generators. Other chapters are dedicated to two new topics, the thermodynamics of the early universe and the Monte Carlo and molecular dynamics simulations. This book is invaluable to students and practitioners interested in statistical mechanics and physics.

  • Practical Business Statistics

    • 6th Edition
    • Andrew F. Siegel
    • English
    Practical Business Statistics, Sixth Edition, is a conceptual , realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize, mathematical correctness. The book offers a deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results. The text uses excellent examples with real world data relating to the functional areas within Business such as finance, accounting, and marketing. It is well written and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details. This edition features many examples and problems that have been updated with more recent data sets, and continues to use the ever-changing Internet as a data source. Supplemental materials include companion website with datasets and software. Each chapter begins with an overview, showing why the subject is important to business, and ends with a comprehensive summary, with key words, questions, problems, database exercises, projects, and cases in most chapters. This text is written for the introductory business/management statistics course offered for undergraduate students or Quantitative Methods in Management/ Analytics for Managers at the MBA level.