Essential Statistical Concepts for the Quality Professional, Stamatis, D. H.
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Boos Название: Essential Statistical Inference ISBN: 1461448174 ISBN-13(EAN): 9781461448174 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Поставка под заказ. Описание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.
Автор: Bhattacharyya Название: Statistical Concepts & Methods (WSE) ISBN: 0471072044 ISBN-13(EAN): 9780471072041 Издательство: Wiley Рейтинг: Цена: 248110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A non--mathematical introductory statistics text that combines clear explanation of concepts, an extensive coverage of useful statistical techniques, and numerous illustrations with live data from diverse fields. Emphasizes assumptions and limitations of the statistical methods so that violations of assumptions can be avoided.
Автор: Hahs-vaughn, Debbie L. (university Of Central Florida, Usa) Lomax, Richard G. (the Ohio State University, Usa) Название: Statistical concepts - a second course ISBN: 0367204096 ISBN-13(EAN): 9780367204099 Издательство: Taylor&Francis Рейтинг: Цена: 78590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Statistical Concepts: A Second Course presents the advanced chapters from An Introduction to Statistical Concepts, 4th Edition, designed for second and upper level statistics courses.
Автор: Hahs-vaughn, Debbie L. (university Of Central Florida, Usa) Lomax, Richard G. (the Ohio State University, Usa) Название: Statistical concepts - a second course ISBN: 0367204045 ISBN-13(EAN): 9780367204044 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Невозможна поставка. Описание: Statistical Concepts: A Second Course presents the advanced chapters from An Introduction to Statistical Concepts, 4th Edition, designed for second and upper level statistics courses.
Автор: Hahs-Vaughn Debbie L Название: Statistical Concepts - A First Course ISBN: 0367203995 ISBN-13(EAN): 9780367203993 Издательство: Taylor&Francis Рейтинг: Цена: 59190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Statistical Concepts: A First Course presents the introductory chapters from An Introduction to Statistical Concepts, 4th Edition, designed for first and lower level statistics courses.
Автор: Lomax, Richard G (the Ohio State University, Usa) Hahs-vaughn, Debbie L. Hahs-vaughn, Debbie L. (university Of Central Florida, Usa) Lomax, Richard G. Название: Introduction to statistical concepts ISBN: 1138650552 ISBN-13(EAN): 9781138650558 Издательство: Taylor&Francis Рейтинг: Цена: 122490.00 T Наличие на складе: Невозможна поставка. Описание: This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results.
Автор: Hahs-Vaughn, Debbie L. , Lomax, Richard G. Название: Statistical Concepts - A First Course ISBN: 0367203960 ISBN-13(EAN): 9780367203962 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Невозможна поставка. Описание: Statistical Concepts: A First Course presents the introductory chapters from An Introduction to Statistical Concepts, 4th Edition, designed for first and lower level statistics courses.
Автор: Farebrother, R.W. , Schyns, Michael Название: Visualizing Statistical Models And Concepts ISBN: 0367447053 ISBN-13(EAN): 9780367447052 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, the author finds that many of the important concepts of mathematical statistics can be associated with physical models; and that the optimality criteria of statistical estimation procedures can often be interpreted in terms of the concept of potential energy.
Автор: James Gareth Название: An Introduction to Statistical Learning ISBN: 1461471370 ISBN-13(EAN): 9781461471370 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Невозможна поставка. Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
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