9781118010648-1118010647-Data Analysis: What Can Be Learned From the Past 50 Years

Data Analysis: What Can Be Learned From the Past 50 Years

ISBN-13: 9781118010648
ISBN-10: 1118010647
Edition: 1
Author: Huber, Peter J.
Publication date: 2011
Publisher: Wiley
Format: Hardcover 234 pages
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Book details

ISBN-13: 9781118010648
ISBN-10: 1118010647
Edition: 1
Author: Huber, Peter J.
Publication date: 2011
Publisher: Wiley
Format: Hardcover 234 pages

Summary

Acknowledged authors Huber, Peter J. wrote Data Analysis: What Can Be Learned From the Past 50 Years comprising 234 pages back in 2011. Textbook and eTextbook are published under ISBN 1118010647 and 9781118010648. Since then Data Analysis: What Can Be Learned From the Past 50 Years textbook was available to sell back to BooksRun online for the top buyback price of $ 2.19 or rent at the marketplace.

Description

This book explores the many provocative questions concerning the fundamentals of 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 be taught? 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 used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniques is not of immediate value; 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.

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