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Visualizing Data Hardcover – 1 March 1993

4.7 out of 5 stars 16 ratings
Edition: 1st

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Review

This book presents a set of graphical
methods for displaying data. The methods are
shown in use in practical examples and their
construction and properties are explained in
this context. The book presents a powerful
display of their use, not in isolation, but
in conjunction with other graphics and in
the context of a serious effort to produce
a coherent data analysis. --Journal of the Amerian Statistical Association<br \><br \>This is a terrific book --- in my opinion,
a pathbreaking book. Get it. Read it.
Practice what it preaches. You will improve
the quality of your data analysis. --Technometrics<br \><br \>Visualizing Data should be required
reading for every scientist and always
should be kept in easy reach. Anyone
with a familiarity with basic statistical
techniques and least-squares methods of
fitting regression lines to data should have
no trouble with the material presented. --BioScience

Visualizing Data should be required
reading for every scientist and always
should be kept in easy reach. Anyone
with a familiarity with basic statistical
techniques and least-squares methods of
fitting regression lines to data should have
no trouble with the material presented. --BioScience

This book presents a set of graphical
methods for displaying data. The methods are
shown in use in practical examples and their
construction and properties are explained in
this context. The book presents a powerful
display of their use, not in isolation, but
in conjunction with other graphics and in
the context of a serious effort to produce
a coherent data analysis. --Journal of the Amerian Statistical Association

About the Author

William S. Cleveland is the Shanti
S. Gupta Distinguished Professor at
Purdue University, and splits his time
between the Statistics and Computer Science
Departments. Throughout his career, he has
worked in research areas --- statistical
model building, local machine learning,
visualization, time series, and data
mining --- that have broadened the scope
of research in learning from data. He has
developed theories and methods that are
now part of the fundamental knowledge base
of data visualization. He has developed
fundamental tools of machine learning that
were subsequently intensively studied by
researchers both in statistics and computer
science, and widely used by the scientific
community.

Cleveland has published over 100 papers on
his research in a wide range of scientific
journals, books, and proceedings. His two
books, The Elements of Graphing Data and
Visualizing Data have been reviewed in many
journals from a wide variety of disciplines,
and Elements was selected for the Library
of Science.

Cleveland has twice won the Wilcoxon
Prize and once won the Youden prize from
the statistics journal Technometrics. He
is a Fellow of the American Statistical
Association, the Institute of Mathematical
Statistics, and the American Association
of the Advancement of Science, and is
an elected member of the International
Statistical Institute. In 1996 he was
chosen Statistician of the Year by the
Chicago Chapter of the American Statistical
Association.

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Product details

  • Publisher ‏ : ‎ Hobart Press; 1st edition (1 March 1993)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 360 pages
  • ISBN-10 ‏ : ‎ 0963488406
  • ISBN-13 ‏ : ‎ 978-0963488404
  • Dimensions ‏ : ‎ 19.05 x 2.54 x 26.04 cm
  • Customer Reviews:
    4.7 out of 5 stars 16 ratings

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4.7 out of 5 stars
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James
5.0 out of 5 stars Interesting book that takes care to lay things out simply ...
Reviewed in the United Kingdom on 15 March 2017
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ninou
5.0 out of 5 stars An oldie, but a goodie
Reviewed in Canada on 6 February 2019
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Georgios Karakatsanis
5.0 out of 5 stars A classic. Definitely not dated. Sometimes you read ...
Reviewed in the United States on 15 March 2016
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Donald J Cooper
5.0 out of 5 stars Worth the effort
Reviewed in the United States on 25 July 2014
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Patrick E. Martin
5.0 out of 5 stars Fabulous
Reviewed in the United States on 19 April 2013
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