exploring data tables trends von hoaglin david (12 Ergebnisse)

Hardcover. Zustand: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Good. No Jacket. Missing dust jacket; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Very Good. No Jacket. Missing dust jacket; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Very good. Softcover, in very good condition. Covers are clean and glossy. Interiors are clean and free from marks of any kind. We ship books every day from a real brick & mortar bookstore, and this listing was written by an actual person, with the book sitting in front of me for inspection.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In.

Zustand: New. pp. 528.

Kartoniert / Broschiert. Zustand: New. DAVID C. HOAGLIN, PhD, is a Fellow of the American Statistical Association.FREDERICK MOSTELLER, PhD, has been the recipient of several honorary degrees and is a former President of the American Statistical Association.JOHN W. TUKEY, PhD, has received the Na.

Zustand: New. This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. Editor(s): Hoaglin, David C.; Mosteller, Frederick; Tukey, John Wilder. Series: Wiley Series in Probability and Statistics. Num Pages: 528 pages, black & white illustrations. BIC Classification: PB. Category: (P) Professional & Vocational. Dimension: 235 x 158 x 27. Weight in Grams: 732. . 2006. Revised. Paperback. . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. revised edition. 527 pages. 9.00x6.00x1.00 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware - WILEY-INTERSCIENCE PAPERBACK SERIESThe Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.'Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area.'-Technometrics'This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously.'-The StatisticianThis newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.