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Common Errors in Statistics (and How to Avoid Them)
     

Common Errors in Statistics (and How to Avoid Them)

4.3 3
by Phillip I. Good, James W. Hardin
 

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Praise for the Second Edition

"All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice."
Journal of Applied Statistics

". . . a very engaging and valuable book for all who use statistics in any setting."
CHOICE

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Overview

Praise for the Second Edition

"All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice."
Journal of Applied Statistics

". . . a very engaging and valuable book for all who use statistics in any setting."
CHOICE

". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well."
MAA Reviews

Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research.

The Third Edition has been considerably expanded and revised to include:

  • A new chapter on data quality assessment
  • A new chapter on correlated data

  • An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs

  • Revamped exercises with a stronger emphasis on solutions

  • An extended chapter on report preparation

  • New sections on factor analysis as well as Poisson and negative binomial regression

Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.

Editorial Reviews

From the Publisher

“Presented in an easy-to-follow style, this textbook is thought for students and professionals in industry, government, medicine, and the social sciences.”  (Zentralblatt MATH, 1 December 2013)

Product Details

ISBN-13:
9781118211274
Publisher:
Wiley
Publication date:
09/20/2011
Sold by:
Barnes & Noble
Format:
NOOK Book
Pages:
288
File size:
2 MB

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What People are Saying About This

From the Publisher
"The new edition incorporates more graphics and examples using more recent data. … Good's advice is usually wise, and always worth considering. Recommended as stimulating reading for the statistical sophisticate." (Journal of Biopharmaceutical Statistics, January 2010)

Meet the Author

PHILLIP I. GOOD, PhD, is Operations Manager of Statcourse.com, a consulting firm specializing in statistical solutions for industry. He has published more than thirty scholarly works, more than six hundred popular articles, and twenty-one books, including Introduction to Statistics Through Resampling Methods and R/S-PLUS and Introduction to Statistics Through Resampling Methods and Microsoft Office Excel, both published by Wiley.

JAMES W. HARDIN, PhD, is Research Associate Professor and Director of the Biostatistics Collaborative Unit at the University of South Carolina.

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Common Errors in Statistics (and How to Avoid Them) 4.3 out of 5 based on 0 ratings. 3 reviews.
Anonymous More than 1 year ago
Anonymous More than 1 year ago
sergevansteenkiste More than 1 year ago
Phillip Good and James Hardin often succeed in their endeavor to make their content accessible to an audience beyond that of "hardcore" statisticians. Despite their many applications in any modern society, statistics look unappealing to most people. Sometimes, both authors get lost in esoteric debates about some statistical topics that are of limited interest to a wider audience. Furthermore, Good and Hardin give too many examples that are related to the medical field. The authors could diversify their examples in a fourth edition of their treatise to further expand their readership. To their credit, Good and Hardin repeatedly warn their audience against the servile reliance on statistical software. Software users have to check the default settings to see if they are applicable to the application at hand. The authors correctly note that the most common error in statistics is to assume that statistical procedures can take the place of sustained effort. For this reason, Good and Hardin urge their readers not to let statistics and by extension statistical software do their thinking for them. In conclusion, "Common Errors in Statistics and How to Avoid Them" is a nice addition to anyone's modeling / statistical library.