- Used Books
- Kobo eReading
- Staff Picks
- Gifts & Gift Cards
- Sell Books
- Stores & Events
Special Offers see all
More at Powell's
Recently Viewed clear list
New Trade Paper
Ships in 1 to 3 days
available for shipping or prepaid pickup only
Available for In-store Pickup
in 7 to 12 days
More copies of this ISBN
Common Errors in Statistics (and How to Avoid Them)by Phillip I. Good
Synopses & Reviews
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."
"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."
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:
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.
The Fourth Edition of this tried-and-true book elaborates on many key topics such as epidemiological studies, distribution of data; baseline data incorporation; case control studies; simulations; statistical theory publication; biplots; instrumental variables; ecological regression; result reporting, survival analysis; etc. Including new modifications and figures, the book also covers such topics as research plan creation; data collection; hypothesis formulation and testing; coefficient estimates; sample size specifications; assumption checking; p-values interpretations and confidence intervals; counts and correlated data; model building and testing; Bayes' Theorem; bootstrap and permutation tests; and more.
About the Author
PHILLIP I. GOOD, PhD, is Operations Manager at Information Research, a consulting firm specializing in statistical solutions for private and public organizations. He has published more than thirty scholarly works and more than 600 popular articles. Dr. Good is the author of Introduction to Statistics Through Resampling Methods and R/S-PLUS®, Introduction to Statistics Through Resampling Methods and Microsoft Office Excel®, and Analyzing the Large Number of Variables in Biomedical and Satellite Imagery, all published by Wiley.
JAMES W. HARDIN, PhD, is Associate Professor and Biostatistics Division Director of the Department of Epidemiology and Biostatistics at the University of South Carolina. Dr. Hardin has published extensively in his areas of research interest, which include generalized linear models, generalized estimating equations, survival models, and computational statistics. He is also an affiliate faculty member of the Institute for Families in Society at the University of South Carolina.
Table of Contents
PART I FOUNDATIONS 1
1. Sources of Error 3
2. Hypotheses: The Why of Your Research 15
3. Collecting Data 31
PART II STATISTICAL ANALYSIS 57
4. Data Quality Assessment 59
5. Estimation 65
6. Testing Hypotheses: Choosing a Test Statistic 79
7. Strengths and Limitations of Some Miscellaneous Statistical Procedures 119
8. Reporting Your Results 139
9. Interpreting Reports 165
10. Graphics 181
PART III BUILDING A MODEL 213
11. Univariate Regression 215
12. Alternate Methods of Regression 237
13. Multivariable Regression 251
14. Modeling Counts and Correlated Data 267
15. Validation 277
Author Index 319
Subject Index 329
What Our Readers Are Saying
Science and Mathematics » Materials Science » General
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics