Author: Phillip I. Good
Publisher: John Wiley & Sons
ISBN: 0471998516
Category : Mathematics
Languages : en
Pages : 268
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Book Description
Praise for the First Edition of Common Errors in Statistics " . . . 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.
Author: Phillip I. Good
Publisher: John Wiley & Sons
ISBN: 1118211278
Category : Mathematics
Languages : en
Pages : 231
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Book Description
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.
Author: Phillip I. Good
Publisher: Wiley-Interscience
ISBN: 9780470388105
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This set contains: 9780471794318 Common Errors in Statistics (and How to Avoid Them), 2nd Edition and 9780471715757 Introduction to Statistics Through Resampling Methods and R/S Plus?? both by Phillip I. Good and James W. Hardin.
Author: Phillip I. Good
Publisher: Wiley
ISBN: 9780470555798
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-45798-6) and Introduction to Statistics Through Resampling Methods and R/S-PLUS (978-0-471-71575-7)
Author: Phillip I. Good
Publisher: Wiley
ISBN: 9780470555897
Category : Mathematics
Languages : en
Pages : 504
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Book Description
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-48798-6)and Introduction to Statistics Through Resampling Methods and Microsoft Office Excel by Phillip I. Good (978-0-471-73191-7)
Author: Fuchang Liu
Publisher: Routledge
ISBN: 1315511754
Category : Education
Languages : en
Pages : 236
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Book Description
Learn the most effective ways to teach elementary math, no matter how much experience you have with the subject. In this book, Fuchang Liu takes you through many common mistakes in math instruction and explains the misunderstandings behind them. He points out practices that should be avoided, helping you to adjust your lessons so that all students can achieve success. You’ll discover how to... - Increase your confidence with core math principles and reasoning - Set your students on the path toward eventually developing more complex math skills - Improve student achievement by approaching problems in logical yet creative ways - Overcome common challenges faced by students and teachers - Teach problem solving for different learning styles Every chapter reconsiders well-established ways of teaching all areas of elementary math, from addition and subtraction to statistics and graphs. Helpful examples and tips are scattered throughout the book, offering revisions to the way these topics are often presented in the classroom. Also included are group study ideas for principals and instructional coaches so your school or district can work on the book together. With this practical guide, you’ll be ready to help students truly develop their math understanding.
Author: Phillip I. Good
Publisher: Wiley
ISBN: 9780470556047
Category : Mathematics
Languages : en
Pages : 545
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Book Description
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-45798-6) and Statistical Rules of Thumb, Second Edition by Gerald van Belle (978-0-470-1448-0)
Author: Michael Borenstein
Publisher:
ISBN: 9781733436700
Category : Meta-analysis
Languages : en
Pages : 409
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Book Description
Author: Alex Reinhart
Publisher: No Starch Press
ISBN: 1593276206
Category : Mathematics
Languages : en
Pages : 177
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Book Description
Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.
Author: Phillip I. Good
Publisher: John Wiley & Sons
ISBN: 0471463779
Category : Mathematics
Languages : en
Pages : 236
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Book Description
A guide to choosing and using the right techniques High-speed computers and prepackaged statistical routines would seem to take much of the guesswork out of statistical analysis and lend its applications readily accessible to all. Yet, as Phillip Good and James Hardin persuasively argue, statistical software no more makes one a statistician than a scalpel makes one a surgeon. Choosing the proper technique and understanding the analytical context is of paramount importance to the proper application of statistics. The highly readable Common Errors in Statistics (and How to Avoid Them) provides both newly minted academics and professionals who use statistics in their work with a handy field guide to statistical problems and solutions. Good and Hardin begin their handbook by establishing a mathematically rigorous but readily accessible foundation for statistical procedures. They focus on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. A handy checklist is provided to summarize the necessary steps. Topics covered include: * 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 others Common Errors in Statistics (and How to Avoid Them) also contains reprints of classic articles from statistical literature to re-examine such bedrock subjects as linear regression, the analysis of variance, maximum likelihood, meta-analysis, and the bootstrap. With a final emphasis on finding solutions and on the great value of statistics when applied in the proper context, this book will prove eminently useful to students and professionals in the fields of research, industry, medicine, and government.
