Common Errors in Statistics (and How to Avoid Them)

Phillip I. Good, James W. Hardin

254 pages, parution le 29/06/2006 (2^eme édition)

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Résumé

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.

L'auteur - Phillip I. Good

PHILLIP I. GOOD, PhD, is an Operations Manager for Information Research in Huntington Beach, California. He is the author of A Manager's Guide to the Design and Conduct of Clinical Trials, published by Wiley, as well as numerous other books.

L'auteur - James W. Hardin

JAMES W. HARDIN, PhD, is a lecturer and Assistant Research Scientist in the Department of Statistics at Texas A&M University.

Sommaire

Foundations
- Sources of Error
- Decisions
- Collecting Data
Hypothesis Testing and Estimation
- Estimation
- Testing Hypotheses: Choosing a Test Statistic
- Miscellaneous Statistical Procedures
- Reporting Results: P-values, Confidence Intervals
- Interpreting Reports
- Graphics
Building a Model
- Univariate Regression
- Alternate Modeling Methods
- Multivariate Regression
- Validation
- Appendix A
- Appendix B
- Glossary: Grouped by Related but Distinct Terms

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Phillip I. Good, James W. Hardin
Parution	29/06/2006
Édition	2^eme édition
Nb. de pages	254
Format	15,5 x 23
Couverture	Broché
Poids	435g
Intérieur	Noir et Blanc
EAN13	9780471794318
ISBN13	978-0-471-79431-8