دانلود کتاب Statistics: Methods and Applications

Книга Statistics: Methods and Applications Statistics: Methods and Applications Книги Математика Автор: Thomas Hill, Paul Lewicki Год издания: 2005 Формат: pdf Издат.:StatSoft, Inc. Страниц: 800 Размер: 5,7 ISBN: 1884233597 Язык: Английский0 (голосов: 0) Оценка:A comprehensive textbook on statistics written for both novices and advanced analysts. This – one of a kind – book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner (“consumer”) of these methods. The primary emphasis is on applications rather than theoretical derivations and formulas. The authors, experienced researchers, draw on their diverse experiences as teachers of quantitative methods at the graduate and undergraduate levels with extensive, real-life consulting expertise (they have been involved in hundreds of projects in various areas of science, business, and industry, on all continents). History of this book. The earlier editions of this unique book were available for over 10 years on the Internet, where it has earned praise from thousands of readers and benefited from their comments, questions, and requests for coverage of specific topics. The electronic version of this textbook has also won the prestigious distinction of becoming the only Internet resource on statistics and data analysis recommended by Encyclopedia Britannica. From a “Novice” to Advanced Analyst. This book was written without assuming that the reader has any prior knowledge of statistics. Instead, it successfully guides the reader all the way from the basic foundations of statistical reasoning, to the most advanced, cutting-edge methods. It includes hundreds of examples and thousands of illustrations created with leading edge data visualization and data mining software. This unusually comprehensive book includes also chapters on industrial statistics, on the emerging areas of predictive analytics, data mining and text mining, and a 200-page, illustrated Glossary of statistical terms.