Common Errors in Statistics
Language: English
Published by Wiley-Interscience, 2006
- Softcover
- Used
Condition: Used - Fine
US$ 15.55
Quantity: 1 available
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Leichte Kratzer / Abnutzungen / Druckstellen; Leichte Gebrauchsspuren; Leichte Verformung / umgeknickte Seiten. Praise for the First Edition highlights its broad appeal to anyone interacting with statistics, regardless of their expertise. The book serves as a guide for those who define good statistical practice, making it a valuable reference for statisticians and researchers alike. Readers have found it highly informative and enjoyable, with particular commendation for its readability. Now in its Second Edition, this guide provides a mathematically rigorous yet accessible foundation for understanding statistical procedures and solutions. It analyzes common mistakes, debunks myths, and assists readers in selecting the most effective statistical techniques for their tasks. Targeted at both new academics and professionals, it covers essential topics such as research planning, hypothesis formulation, sample size specification, assumption checking, p-value interpretation, model building, data mining, and Bayes' Theorem. The extensively revised Second Edition includes additional charts and graphs, two new chapters--Interpreting Reports and Which Regression Method?--and sections on practical versus statistical significance and nonuniqueness in multivariate regression. It also incorporates material from the authors' online courses and addresses unbalanced designs and alternative modeling methods. Emphasizing the value of statistics when applied correctly, this book is an essential resource for students and professionals in research, industry. …
Seller Inventory # 8895c666-7544-4808-99d3-76ab5a156f23
- Title
- Common Errors in Statistics
- Author
- Phillip I. Good
- Publisher
- Wiley-Interscience
- Publication year
- 2006
- Condition
- Fine
- Binding
- Softcover
- Language
- English
- ISBN 10
- 0471794317
- ISBN 13
- 9780471794318
- Edition
- 2nd Edition
" . . . let me recommend Common Errors to all those who interact with statistics, whatever their level of statistical understanding . . . "
--Stats 40
" . . . written . . . for the people who define good practice rather than seek to emulate it."
--Journal of Biopharmaceutical Statistics
" . . . highly informative, enjoyable to read, and of potential use to a broad audience. It is a book that should be on the reference shelf of many statisticians and researchers."
--The American Statistician
" . . . I found this book the most easily readable statistics book ever. The credit for this certainly goes to Phillip Good."
--E-STREAMS
A tried-and-true guide to the proper application of statistics
Now in a second edition, the highly readable Common Errors in Statistics (and How to Avoid Them) lays a mathematically rigorous and readily accessible foundation for understanding statistical procedures, problems, and solutions. This handy field guide analyzes common mistakes, debunks popular myths, and helps readers to choose the best and most effective statistical technique for each of their tasks.
Written for both the newly minted academic and the professional who uses statistics in their work, the book covers creating a research plan, formulating a hypothesis, specifying sample size, checking assumptions, interpreting p-values and confidence intervals, building a model, data mining, Bayes' Theorem, the bootstrap, and many other topics. The Second Edition has been extensively revised to include:
* Additional charts and graphs
* Two new chapters, Interpreting Reports and Which Regression Method?
* New sections on practical versus statistical significance and nonuniqueness in multivariate regression
* Added material from the authors' online courses at statistics.com
* New material on unbalanced designs, report interpretation, and alternative modeling methods
With a final emphasis on both finding solutions and the great value of statistics when applied in the proper context, this book is eminently useful to students and professionals in the fields of research, industry, medicine, and government.
"Synopsis" may belong to another edition of this title.
About the Author
JAMES W. HARDIN, PhD, is Associate Research Professor in the Department of Epidemiology and Biostatistics at the University of South Carolina.
"About the title" may belong to another edition of this title.
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