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Common Errors in Statistics (and How to Avoid Them), 4th Edition

Posted By: ksveta6
Common Errors in Statistics (and How to Avoid Them), 4th Edition

Common Errors in Statistics (and How to Avoid Them) by Phillip I. Good, James W. Hardin
2012 | ISBN: 1118294394 | English | 352 pages | EPUB | 4 MB

Praise for Common Errors in Statistics (and How to Avoid Them)

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

"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."
—MAA Reviews

Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials.

Providing a consistent level of coherency throughout, the highly readable Fourth Edition focuses on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. The authors begin with an introduction to the main sources of error and provide techniques for avoiding them. Subsequent chapters outline key methods and practices for accurate analysis, reporting, and model building. The Fourth Edition features newly added topics, including:

Baseline data
Detecting fraud
Linear regression versus linear behavior
Case control studies
Minimum reporting requirements
Non-random samples
The book concludes with a glossary that outlines key terms, and an extensive bibliography with several hundred citations directing readers to resources for further study.

Presented in an easy-to-follow style, Common Errors in Statistics, Fourth Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.