This book explores the many provocative questions concerning the fundamentalsof data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it betaught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if usedat all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses inthis volume. Concern with specific statistical techniques is not of immediatevalue; rather, questions of strategy - when to use which technique - are employed. Central to the discussion is an understanding of the significance of massive (or robust) data sets, the implementation of languages, and the use of models. Each is sprinkled with an ample number of examples and case studies. Personal practices, various pitfalls, and existing controversies are presented when applicable. The book serves as an excellent philosophical and historical companion to any present-day text in data analysis, robust statistics, data mining, statistical learning, or computational statistics
- ISBN: 978-1-1180-1064-8
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 240
- Fecha Publicación: 18/03/2011
- Nº Volúmenes: 1
- Idioma: Inglés