A Practical Introduction to Index Numbers


Book Description

This book provides an introduction to index numbers for statisticians, economists and numerate members of the public. It covers the essential basics, mixing theoretical aspects with practical techniques to give a balanced and accessible introduction to the subject. The concepts are illustrated by exploring the construction and use of the Consumer Prices Index which is arguably the most important of all official statistics in the UK. The book also considers current issues and developments in the field including the use of large-scale price transaction data. A Practical Introduction to Index Numbers will be the ideal accompaniment for students taking the index number components of the Royal Statistical Society Ordinary and Higher Certificate exams; it provides suggested routes through the book for students, and sets of exercises with solutions.







Introduction to Indexing and Abstracting


Book Description

Based on new research and years of practical experience, this guide presents the basic knowledge necessary to become a professional indexer. Synthesizing the thinking and experience of indexers and abstractors over the years, the book introduces readers to such fundamentals as the nature of information, the organization of information, vocabulary control, types of indexes and abstracts, evaluation of indexing, and the use of computers. A new chapter on indexing and the Internet has been added, as has a chapter that lists Web resources for indexers and abstractors. The work concludes with a discussion of the education, training, and job opportunities of the profession, as well as a look to the future. With its simple but thorough approach, this book provides readers with a broad overview of the professions, processes, and art of indexing and abstracting.




Indexing Books, Second Edition


Book Description

Since 1994, Nancy Mulvany's Indexing Books has been the gold standard for thousands of professional indexers, editors, and authors. This long-awaited second edition, expanded and completely updated, will be equally revered. Like its predecessor, this edition of Indexing Books offers comprehensive, reliable treatment of indexing principles and practices relevant to authors and indexers alike. In addition to practical advice, the book presents a big-picture perspective on the nature and purpose of indexes and their role in published works. New to this edition are discussions of "information overload" and the role of the index, open-system versus closed-system indexing, electronic submission and display of indexes, and trends in software development, among other topics. Mulvany is equally comfortable focusing on the nuts and bolts of indexing—how to determine what is indexable, how to decide the depth of an index, and how to work with publisher instructions—and broadly surveying important sources of indexing guidelines such as The Chicago Manual of Style, Sun Microsystems, Oxford University Press, NISO TR03, and ISO 999. Authors will appreciate Mulvany's in-depth consideration of the costs and benefits of preparing one's own index versus hiring a professional, while professional indexers will value Mulvany's insights into computer-aided indexing. Helpful appendixes include resources for indexers, a worksheet for general index specifications, and a bibliography of sources to consult for further information on a range of topics. Indexing Books is both a practical guide and a manifesto about the vital role of the human-crafted index in the Information Age. As the standard indexing reference, it belongs on the shelves of everyone involved in writing and publishing nonfiction books.




Introduction to Information Retrieval


Book Description

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.




Beyond Book Indexing


Book Description

How to get started in web indexing, embedded indexing, and other computer-based media.




The Atiyah-Singer Index Theorem


Book Description




Indexing and Retrieval of Non-Text Information


Book Description

The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.




An Introduction to Statistical Learning


Book Description

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.




Chaos: A Mathematical Introduction


Book Description

When new ideas like chaos first move into the mathematical limelight, the early textbooks tend to be very difficult. The concepts are new and it takes time to find ways to present them in a form digestible to the average student. This process may take a generation, but eventually, what originally seemed far too advanced for all but the most mathematically sophisticated becomes accessible to a much wider readership. This book takes some major steps along that path of generational change. It presents ideas about chaos in discrete time dynamics in a form where they should be accessible to anyone who has taken a first course in undergraduate calculus. More remarkably, it manages to do so without discarding a commitment to mathematical substance and rigour. The book evolved from a very popular one-semester middle level undergraduate course over a period of several years and has therefore been well class-tested.