Handbooks, dictionaries and encyclopedias

The Handbook of Computational Statistics - Concepts and Methods (second edition) is divided into 4 parts. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.

Practical Statistics is an introduction and reference guide which gives the reader a solid understanding of statistics without being too simple or mind-numbingly complex. It turns statistics, into something approachable and sensible by emphasizes the importance of working back from results rather than working out results. With basic concepts that get increasingly more complex, simple diagrams to multivariate methods, as well as using simple metaphors to aid understanding. The book has a two-level approach, with sections headed 'The essentials' and 'Tell me more' to support learning at all levels.

This Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.

A Handbook of Statistical Analyses using R provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.

Schaum's Outlines presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills.

A concise introduction into fundamental concepts in statistics. Chapter 1: Short exposition of probability theory, using generic examples. Chapter 2: Estimation in theory and practice, using biologically motivated examples. Maximum-likelihood estimation in covered, including Fisher information and power computations. Methods for calculating confidence intervals and robust alternatives to standard estimators are given. Chapter 3: Hypothesis testing with emphasis on concepts, particularly type-I , type-II errors, and interpreting test results. Several examples are provided. T-tests are used throughout, followed important other tests and robust/nonparametric alternatives. Multiple testing is discussed in more depth, and combination of independent tests is explained. Chapter 4: Linear regression, with computations solely based on R. Multiple group comparisons with ANOVA are covered together with linear contrasts, again using R for computations.

This dictionary is authoritative, reliable and provides jargon-free definitions for even the most technical mathematical terms. With over 3,000 entries ranging from Achilles paradox to zero matrix, it covers all commonly encountered terms and concepts from pure and applied mathematics and statistics, for example, linear algebra, optimisation, nonlinear equations, and differential equations. In addition, there are entries on major mathematicians and on topics of more general interest, such as fractals, game theory, and chaos. Usinggraphs, diagrams, and charts to render definitions as comprehensible as possible, entries are clear and accessible. Almost 200 new entries have been added to this edition, including terms such as arrow paradox, nested set, and symbolic logic.

This wide-ranging, jargon-free dictionary contains over 2,300 entries on all aspects of statistics, including terms used in computing, mathematics, and probability. While embracing the whole multi-disciplinary spectrum of this complex subject, information is presented in a clear and practical manner.

This book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis. b) to enable any non-statistician to obtain quick and yet comprehensive and highly understandable view on certain statistical term, method or application c) to enable all the researchers, managers and practicioners to refresh their knowledge in Statistics, especially in certain controversial fields. d) to revive interest in statistics among students, since they will see its usefulness and relevance in almost all branches of Science.

This source of information on statistical theory, methods, and applications is designed to bring the encyclopedia in line with the latest topics and advances made in statistical science over the past decade--in areas such as computer-intensive statistical methodology, genetics, medicine, the environment, and other applications. Written by over 600 world-renowned experts (including the editors), the entries are self-contained and easily understood by readers with a limited statistical background. With the publication of this second edition in 16 printed volumes, the Encyclopedia of Statistical Sciences retains its position as a cutting-edge reference of choice for those working in statistics, biostatistics, quality control, economics, sociology, engineering, probability theory, computer science, biomedicine, psychology, and many other areas.

The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics. The reference is alphabetically arranged to provide quick access to the fundamental tools of statistical methodology and biographies of famous statisticians. The more than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions. This reference will be an enduring resource for locating convenient overviews about this essential field of study.